Path providing device and path providing method thereof

ABSTRACT

A path providing device configured to provide a path information to a vehicle includes a communication unit configured to receive, from a server, map information including a plurality of layers of data, an interface unit configured to receive sensing information from one or more sensors disposed at the vehicle, and a processor. The processor is configured to determine an optimal path for guiding the vehicle from an identified lane, generate autonomous driving visibility information based on the sensing information and the determined optimal path, update the optimal path based on dynamic information related to a movable object located on the optimal path and the autonomous driving visibility information, receive different types of sensor data from a plurality of sensors, and update at least one of the autonomous driving visibility information or the optimal path based on information generated by combining at least two types of sensor data.

CROSS-REFERENCE TO RELATED APPLICATIONS

Pursuant to 35 U.S.C. § 119(e), this application is a continuation ofInternational Application PCT/KR2019/011424, with an internationalfiling date of Sep. 4, 2019, which is hereby incorporated by referenceherein in its entirety.

TECHNICAL FIELD

The present disclosure relates to a path providing device providing apath (route) to a vehicle and a path providing method thereof.

BACKGROUND

A vehicle refers to means of transporting people or goods by usingkinetic energy. Representative examples of vehicles include automobilesand motorcycles.

For safety and convenience of a user who uses the vehicle, varioussensors and devices are provided in the vehicle, and functions of thevehicle are diversified.

The functions of the vehicle may be divided into a convenience functionfor promoting driver's convenience, and a safety function for enhancingsafety of the driver and/or pedestrians.

First, the convenience function has a development motive associated withthe driver's convenience, such as providing infotainment(information+entertainment) to the vehicle, supporting a partiallyautonomous driving function, or helping the driver ensuring a field ofvision at night or at a blind spot. For example, the conveniencefunctions may include various functions, such as an active cruisecontrol (ACC), a smart parking assist system (SPAS), a night vision(NV), a head up display (HUD), an around view monitor (AVM), an adaptiveheadlight system (AHS), and the like.

The safety function is a technique of ensuring safeties of the driverand/or pedestrians, and may include various functions, such as a lanedeparture warning system (LDWS), a lane keeping assist system (LKAS), anautonomous emergency braking (AEB), and the like.

For the convenience of a user using a vehicle, various types of sensorsand electronic devices are provided in the vehicle. Specifically, astudy on an Advanced Driver Assistance System (ADAS) is activelyundergoing. In addition, an autonomous vehicle is actively underdevelopment.

As the development of the advanced driver assistance system (ADAS) isactively undergoing in recent time, development of a technology foroptimizing user's convenience and safety while driving a vehicle isrequired.

As part of this effort, in order to effectively transmit electronicHorizon (eHorizon) data to autonomous driving systems and infotainmentsystems, the European Union Original Equipment Manufacturing (EU OEM)Association has established a data specification and transmission methodas a standard under the name “Advanced Driver Assistance SystemsInterface Specification (ADASIS).”

In addition, eHorizon (software) is becoming an integral part ofsafety/ECO/convenience of autonomous vehicles in a connectedenvironment.

SUMMARY

The present disclosure describes a path providing device configured toprovide autonomous driving visibility information allowing autonomousdriving, and a path providing method thereof.

The present disclosure also describes a path providing device capable ofupdating autonomous driving visibility information and an optimal pathusing a plurality of sensors in an optimized manner, and a pathproviding method thereof.

The present disclosure further describes a path providing device capableof updating autonomous driving visibility information and an optimalpath in an optimized manner using optimized sensor data depending onsituations, and a path providing method thereof.

The present disclosure further describes a path providing device capableof updating autonomous driving visibility information and an optimalpath in a different manner depending on a sensor sensing range, and apath providing method thereof.

According to one aspect of the subject matter described in thisapplication a path providing device configured to provide a pathinformation to a vehicle includes a communication unit configured toreceive, from a server, map information including a plurality of layersof data, an interface unit configured to receive sensing informationfrom one or more sensors disposed at the vehicle, the sensinginformation including an image received from an image sensor, and aprocessor. The processor may be configured to identify a lane in whichthe vehicle is located among a plurality of lanes of a road based on thesensing information, determine an optimal path for guiding the vehiclefrom the identified lane, the optimal path comprising one or more lanesincluded in the map information, generate autonomous driving visibilityinformation and transmit the generated autonomous driving visibilityinformation to at least one of the server or an electric componentdisposed at the vehicle based on the sensing information and thedetermined optimal path, and update the optimal path based on dynamicinformation related to a movable object located on the optimal path andthe autonomous driving visibility information. The processor may befurther configured to receive different types of sensor data from aplurality of sensors disposed at the vehicle, and update at least one ofthe autonomous driving visibility information or the optimal path basedon information generated by combining at least two types of sensor data.

Implementations according to this aspect may include one or more of thefollowing features. For example, the processor may be configured todivide the optimal path into a plurality of sections according tocharacteristics of the optimal path, determine a plurality of sensors tobe used in each section based on a characteristic associated with eachof the plurality of sections, and update the autonomous drivingvisibility information based on sensor data sensed by the determined theplurality of sensors.

In some examples, the processor may be configured to determine a sectionset to use the determined plurality of sensors based on a type of eachof the determined plurality of sensors, and update the autonomousdriving visibility information by fusing a plurality of sensor dataacquired by the plurality of sensors, based on an arrival at thedetermined section. In some examples, the characteristic may bedetermined based on at least one of a road shape or time.

In some implementations, the processor may be configured to update theautonomous driving visibility information according to situations, using(i) information included within a predetermined range set based on theoptimal path in the map information and (ii) information generated byfusing the at least two types of sensor data. In some implementations,the processor may be configured to determine a plurality of sensors thatcan sense currently-required information among the plurality of sensorsbased on the map information, and receive the at least two types ofsensor data from the determined plurality of sensors.

In some examples, the processor may be configured to generateinformation necessary for a situation that the vehicle is currentlyfacing, by processing the received sensor data, based on the at leasttwo types of sensor data being received, and update the autonomousdriving visibility information by adding the generated information tothe map information.

In some implementations, the processor may be configured to recognizedifferent characteristics of a specific object using a plurality ofsensor data. In some examples, the processor may be configured todetermine a type of the specific object based on first sensor data ofthe plurality of sensor data, and determine a distance up to thespecific object and a volume of the specific object based on secondsensor data of the plurality of sensor data.

In some examples, the plurality of sensors includes a camera, and theprocessor may be configured to merge object information received throughthe camera with the map information, and update the autonomous drivingvisibility information using a type of the specific object included inthe object information. In some examples, the plurality of sensors mayinclude at least one of a radar or a LIDAR, and the processor may beconfigured to sense information related to a distance to the specificobject and a volume of the specific object through the at least one ofthe radar or the LIDAR, and correct object information included in themap information using the sensed information related to the distance andthe volume.

In some implementations, the processor may be configured to fuse aplurality of sensor data sensed through at least two sensors based on atleast one of a driving speed of the vehicle, a road shape, time, or anexternal environment state, and update the optimal path based on thefused data. In some examples, the processor may be configured to receivethe plurality of sensor data through different sensors, based oninformation related to a type of sensor to be used for each externalenvironment state and a type of sensor to be used for each road shape.

In some examples, the processor may be configured to receive theplurality of sensor data through different sensors based on at least oneof the external environment state or a shape of a road on which thevehicle is currently located, and selectively merge the receivedplurality of sensor data to update the autonomous driving visibilityinformation.

In some implementations, the processor may be configured to predict anevent to occur on the optimal path based on (i) the autonomous drivingvisibility information, (ii) object information generated by merging aplurality of sensor data received through the plurality of sensors, and(iii) information received from another vehicle through thecommunication unit. In some implementations, the processor may beconfigured to fuse sensor data in a different manner according to asensing range of each of the plurality of sensors.

In some examples, a first sensor of the plurality of sensors may have asensing range of a first radius based on the vehicle, a second sensor ofthe plurality of sensors may have a sensing range of a second radius,the second radius being longer than the first radius from a location ofthe vehicle, and the processor may be configured to fuse sensor datasensed by the first sensor and the second sensor up to the first radiusto update the optimal path using the fused sensor data, and update theoptimal path only using sensor data of the second sensor in a sectionbetween the first radius and the second radius.

According to another aspect of the subject matter described in thisapplication, a path providing method, performed by a path providingdevice configured to provide path information to a vehicle, may includereceiving, from a server, map information including a plurality oflayers of data, receiving, from one or more sensors disposed at thevehicle, sensing information including an image received from an imagesensor, identifying a lane in which the vehicle is located among aplurality of lanes of a road based on the sensing information,determining an optimal path for guiding the vehicle from the identifiedlane, the optimal path comprising one or more lanes included in the mapinformation, generating autonomous driving visibility information andtransmitting the generated autonomous driving visibility information toat least one of the server or an electric component disposed at thevehicle based on the sensing information and the determined optimalpath, updating the optimal path based on dynamic information related toa movable object located in the optimal path and the autonomous drivingvisibility information, receiving different types of sensor data from aplurality of sensors disposed at the vehicle, and updating at least oneof the autonomous driving visibility information or the optimal pathbased on information generated by combining at least two types of sensordata.

Implementations according to this aspect may include one or morefollowing features. For example, the method may further include dividingthe optimal path into a plurality of sections according tocharacteristics of the optimal path, determining a plurality of sensorsto be used in each section based on a characteristic associated witheach of the plurality of sections, and updating the autonomous drivingvisibility information based on sensor data sensed by the determinedplurality of sensors.

In some examples, the method may further include determining a sectionset to use the determined plurality of sensors based on a type of eachof the plurality of sensors, and updating the autonomous drivingvisibility information by fusing a plurality of sensor data acquired bythe plurality of sensors, based on an arrival at the determined section.

The effects of a path providing device and a path providing methodthereof according to the present disclosure will be described.

First, the present disclosure may provide a path providing device thatis optimized for generating or updating autonomous driving visibilityinformation.

Second, the present disclosure may perform update more accurately byupdating autonomous driving visibility information or an optimal pathusing a plurality of sensor data.

Third, the present disclosure may perform optimized update using aplurality of sensor data required according to situations.

Fourth, the present disclosure may provide a new path providing device,capable of updating autonomous driving visibility information or anoptimal path by using a different method of fusing a plurality of sensordata depending on a sensing range of each sensor, and a path providingmethod thereof.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an outer appearance of a vehicle.

FIG. 2 illustrates a vehicle exterior from various angles.

FIGS. 3 and 4 illustrate a vehicle interior.

FIGS. 5 and 6 are diagrams referenced to describe objects.

FIG. 7 is a block diagram of an exemplary vehicle.

FIG. 8 is a diagram of an exemplary Electronic Horizon Provider (EHP).

FIG. 9 is a block diagram of an exemplary path providing device of FIG.8 .

FIG. 10 is a diagram of an exemplary eHorizon.

FIGS. 11A and 11B are diagrams illustrating examples of a Local DynamicMap (LDM) and an Advanced Driver Assistance System (ADAS) MAP.

FIGS. 12A and 12B are diagrams illustrating examples of method ofreceiving high-definition map data by a path providing device of FIG. 8.

FIG. 13 is a flowchart of an exemplary method of generating autonomousdriving visibility information by receiving high-definition map by thepath providing device.

FIGS. 14A and 14B are conceptual views illustrating exemplary types ofsensors of a vehicle that are used in a path providing device.

FIG. 15 is a conceptual view illustrating an exemplary path providingdevice using a plurality of sensor data.

FIG. 16 is a flowchart illustrating an exemplary control method.

FIG. 17 is a conceptual view illustrating the exemplary control methodillustrated in FIG. 16 .

FIGS. 18 to 21 are flowcharts and conceptual views illustrating anexemplary method of updating autonomous driving visibility informationand an optimal path using a plurality of sensor data.

FIG. 22 is a flowchart illustrating an exemplary method of fusing aplurality of sensor data and updating an optimal path according tosensing ranges of sensors in a path providing device.

DETAILED DESCRIPTION

Description will now be given in detail according to exemplaryimplementations disclosed herein, with reference to the accompanyingdrawings. For the sake of brief description with reference to thedrawings, the same or equivalent components may be provided with thesame or similar reference numbers, and description thereof will not berepeated. In general, a suffix such as “module” and “unit” may be usedto refer to elements or components. Use of such a suffix herein ismerely intended to facilitate description of the specification, and thesuffix itself is not intended to give any special meaning or function.In describing the present disclosure, if a detailed explanation for arelated known function or construction is considered to unnecessarilydivert the gist of the present disclosure, such explanation has beenomitted but would be understood by those skilled in the art. Theaccompanying drawings are used to help easily understand the technicalidea of the present disclosure and it should be understood that the ideaof the present disclosure is not limited by the accompanying drawings.The idea of the present disclosure should be construed to extend to anyalterations, equivalents and substitutes besides the accompanyingdrawings.

It will be understood that although the terms first, second, etc. may beused herein to describe various elements, these elements should not belimited by these terms. These terms are generally only used todistinguish one element from another.

It will be understood that when an element is referred to as being“connected with” another element, the element can be connected with theanother element or intervening elements may also be present.

A singular representation may include a plural representation unless itrepresents a definitely different meaning from the context.

Terms such as “include” or “has” are used herein and should beunderstood that they are intended to indicate an existence of severalcomponents, functions or steps, disclosed in the specification, and itis also understood that greater or fewer components, functions, or stepsmay likewise be utilized.

A vehicle according to some implementations of the present disclosuremay be understood as a conception including cars, motorcycles and thelike. Hereinafter, the vehicle will be described based on a car.

The vehicle according to some implementations of the present disclosuremay be a conception including all of an internal combustion engine carhaving an engine as a power source, a hybrid vehicle having an engineand an electric motor as power sources, an electric vehicle having anelectric motor as a power source, and the like.

In the following description, a left side of a vehicle or the likerefers to a left side in a driving direction of the vehicle, and a rightside of the vehicle or the like refers to a right side in the drivingdirection.

As illustrated in FIGS. 1 to 7 , a vehicle 100 may include wheelsturning by a driving force, and a steering input device 510 foradjusting a driving (proceeding, moving) direction of the vehicle 100.

The vehicle 100 may be an autonomous vehicle.

In some implementations, the vehicle 100 may be switched into anautonomous mode or a manual mode based on a user input.

For example, the vehicle 100 may be converted from the manual mode intothe autonomous mode or from the autonomous mode into the manual modebased on a user input received through a user interface apparatus 200 inFIG. 7 .

The vehicle 100 may be switched into the autonomous mode or the manualmode based on driving environment information. The driving environmentinformation may be generated based on object information provided froman object detecting apparatus 300 in FIG. 7 .

For example, the vehicle 100 may be switched from the manual mode intothe autonomous mode or from the autonomous module into the manual modebased on driving environment information generated in the objectdetecting apparatus 300.

In an example, the vehicle 100 may be switched from the manual mode intothe autonomous mode or from the autonomous module into the manual modebased on driving environment information received through acommunication apparatus 400 in FIG. 7 .

The vehicle 100 may be switched from the manual mode into the autonomousmode or from the autonomous module into the manual mode based oninformation, data, or signal provided from an external device.

When the vehicle 100 is driven in the autonomous mode, the vehicle 100may be driven based on an operation system 700.

For example, the autonomous vehicle 100 may be driven based oninformation, data or signal generated in a driving system 710, a parkingexit system 740, and a parking system 750.

When the vehicle 100 is driven in the manual mode, the autonomousvehicle 100 may receive a user input for driving through a drivingcontrol apparatus 500. The vehicle 100 may be driven based on the userinput received through the driving control apparatus 500.

As illustrated in FIG. 7 , the vehicle 100 may include a user interfaceapparatus 200, an object detecting apparatus 300, a communicationapparatus 400, a driving control apparatus 500, a vehicle operatingapparatus 600, an operation system 700, a navigation system 770, asensing unit 120, an interface unit 130, a memory 140, a controller 170,a power supply unit 190, and a path providing device 800.

The vehicle 100 may include more components in addition to thecomponents to be explained in this specification or may exclude one ormore of the components described in this specification.

The user interface apparatus 200 is an apparatus that providescommunication between the vehicle 100 and a user. The user interfaceapparatus 200 may receive a user input and provide information generatedin the vehicle 100 to the user. The vehicle 100 may implement userinterfaces (UIs) or user experiences (UXs) through the user interfaceapparatus 200.

The user interface apparatus 200 may include an input unit 210, aninternal camera 220, a biometric sensing unit 230, an output unit 250,and at least one processor such as a processor 270.

The user interface apparatus 200 may include more components in additionto the components that are described in this specification or mayexclude one or more of those components described in this specification.

The input unit 210 may allow the user to input information. Datacollected in the input unit 210 may be analyzed by the processor 270 andprocessed as a user's control command.

The input unit 210 may be disposed inside the vehicle. For example, theinput unit 210 may be disposed on or around a steering wheel, aninstrument panel, a seat, each pillar, a door, a center console, aheadlining, a sun visor, a wind shield, a window or other suitable areasin the vehicle.

The input unit 210 may include a voice input module 211, a gesture inputmodule 212, a touch input module 213, and a mechanical input module 214.

The voice input module 211 may convert a user's voice input into anelectric signal. The converted electric signal may be provided to theprocessor 270 or the controller 170.

The voice input module 211 may include at least one microphone.

The gesture input module 212 may convert a user's gesture input into anelectric signal. The converted electric signal may be provided to theprocessor 270 or the controller 170.

The gesture input module 212 may include at least one of an infraredsensor or an image sensor for detecting the user's gesture input.

According to some implementations, the gesture input module 212 maydetect a user's three-dimensional (3D) gesture input. For example, thegesture input module 212 may include a light emitting diode outputting aplurality of infrared rays or a plurality of image sensors.

The gesture input module 212 may detect the user's 3D gesture input by atime of flight (TOF) method, a structured light method or a disparitymethod.

The touch input module 213 may convert the user's touch input into anelectric signal. The converted electric signal may be provided to theprocessor 270 or the controller 170.

The touch input module 213 may include a touch sensor for detecting theuser's touch input.

According to an implementation, the touch input module 213 may beintegrated with the display module 251 so as to implement a touchscreen. The touch screen may provide an input interface and an outputinterface between the vehicle 100 and the user.

The mechanical input module 214 may include at least one of a button, adome switch, a jog wheel and a jog switch. An electric signal generatedby the mechanical input module 214 may be provided to the processor 270or the controller 170.

The mechanical input module 214 may be arranged on a steering wheel, acenter fascia, a center console, a cockpit module, a door, and/or othersuitable areas in the vehicle.

The internal camera 220 may acquire an internal image of the vehicle.The processor 270 may detect a user's state based on the internal imageof the vehicle. The processor 270 may acquire information related to theuser's gaze from the internal image of the vehicle. The processor 270may detect a user gesture from the internal image of the vehicle.

The biometric sensing unit 230 may acquire the user's biometricinformation. The biometric sensing unit 230 may include a sensor fordetecting the user's biometric information and acquire fingerprintinformation and heart rate information regarding the user using thesensor. The biometric information may be used for user authentication.

The output unit 250 may generate an output related to a visual, audibleor tactile signal.

The output unit 250 may include at least one of a display module 251, anaudio output module 252, or a haptic output module 253.

The display module 251 may output graphic objects corresponding tovarious types of information.

The display module 251 may include at least one of a liquid crystaldisplay (LCD), a thin film transistor-LCD (TFT LCD), an organiclight-emitting diode (OLED), a flexible display, a three-dimensional(3D) display, and an e-ink display.

The display module 251 may be inter-layered or integrated with a touchinput module 213 to implement a touch screen.

The display module 251 may be implemented as a head up display (HUD).When the display module 251 is implemented as the HUD, the displaymodule 251 may be provided with a projecting module so as to outputinformation through an image which is projected on a windshield or awindow.

The display module 251 may include a transparent display. Thetransparent display may be attached to the windshield or the window.

The transparent display may have a predetermined degree of transparencyand output a predetermined screen thereon. The transparent display mayinclude at least one of a thin film electroluminescent (TFEL), atransparent OLED, a transparent LCD, a transmissive transparent display,and a transparent LED display. The transparent display may haveadjustable transparency.

Meanwhile, the user interface apparatus 200 may include a plurality ofdisplay modules 251 a to 251 g as depicted in FIGS. 3, 4, and 6 .

The display module 251 may be disposed on or around a steering wheel,instrument panels 251 a, 251 b, and 251 e, (as depicted in FIGS. 3, 4,and 6 ), a seat 251 d (as depicted in FIG. 4 ), each pillar 251 f (asdepicted in FIG. 4 ), a door 251 g (as depicted in FIG. 4 ), a centerconsole, a headlining or a sun visor, or implemented on or around awindshield 251 c and/or a window 251 h (as depicted in FIG. 3 ).

The audio output module 252 may convert an electric signal provided fromthe processor 270 or the controller 170 into an audio signal for output.For example, the audio output module 252 may include at least onespeaker.

The haptic output module 253 may generate a tactile output. For example,the haptic output module 253 may vibrate the steering wheel, a safetybelt, a seat 110FL, 110FR, 110RL, 110RR (in FIG. 4 ) such that the usercan recognize such output.

The processor 270 may control an overall operation of each unit of theuser interface apparatus 200.

In some implementations, the user interface apparatus 200 may include aplurality of processors 270 or may not include any processor 270.

When the processor 270 is not included in the user interface apparatus200, the user interface apparatus 200 may operate according to a controlof a processor of another apparatus within the vehicle 100 or thecontroller 170.

The user interface apparatus 200 may also be referred to herein as adisplay apparatus for vehicle.

In some implementations, the user interface apparatus 200 may operateaccording to the control of the controller 170.

Referring still to FIG. 7 , the object detecting apparatus 300 is anapparatus for detecting an object located at outside of the vehicle 100.

The object may be a variety of objects associated with driving oroperation of the vehicle 100.

Referring to FIGS. 5 and 6 , an object O may include traffic lanes OB10,another vehicle OB11, a pedestrian OB12, a two-wheeled vehicle OB13,traffic signals OB14 and OB15, light, a road, a structure, a speed hump,a terrain, an animal, and other objects.

The lane OB10 may be a driving lane, a lane next to the driving lane, ora lane on which another vehicle comes in an opposite direction to thevehicle 100. Each lane OB10 may include left and right lines forming thelane.

The another vehicle OB11 may be a vehicle which is moving near thevehicle 100. The another vehicle OB11 may be a vehicle located within apredetermined distance from the vehicle 100. For example, the anothervehicle OB11 may be a vehicle moving ahead of or behind the vehicle 100.

The pedestrian OB12 may be a person located near the vehicle 100. Thepedestrian OB12 may be a person located within a predetermined distancefrom the vehicle 100. For example, the pedestrian OB12 may be a personlocated on a sidewalk or roadway.

The two-wheeled vehicle OB13 may refer to a vehicle (transportationfacility) that is located near the vehicle 100 and moves using twowheels. The two-wheeled vehicle OB13 may be a vehicle that is locatedwithin a predetermined distance from the vehicle 100 and has two wheels.For example, the two-wheeled vehicle OB13 may be a motorcycle or abicycle that is located on a sidewalk or roadway.

The traffic signals may include a traffic light OB15, a traffic signOB14 and a pattern or text drawn on a road surface.

The light may be light emitted from a lamp provided on another vehicle.The light may be light generated from a streetlamp. The light may besolar light.

The road may include a road surface, a curve, an upward slope, adownward slope and the like.

The structure may be an object that is located near a road and fixed onthe ground. For example, the structure may include a streetlamp, aroadside tree, a building, an electric pole, a traffic light, a bridgeand the like.

The terrain may include a mountain, a hill and the like.

In some implementations, objects may be classified into a moving objectand a fixed object. For example, the moving object may include anothervehicle or a pedestrian. The fixed object may include, for example, atraffic signal, a road, or a structure.

The object detecting apparatus 300 may include a camera 310, a radar320, a LiDAR 330, an ultrasonic sensor 340, an infrared sensor 350, andat least one processor such as a processor 370.

In some implementations, the object detecting apparatus 300 may furtherinclude other components in addition to the components described herein,or may exclude one or more of the components described herein.

The camera 310 may be located on an appropriate portion outside thevehicle to acquire an external image of the vehicle. The camera 310 maybe a mono camera, a stereo camera 310 a (as depicted in FIGS. 1 and 2 ),an around view monitoring (AVM) camera 310 b (as depicted in FIG. 2 ) ora 360-degree camera.

In some implementations, the camera 310 may be disposed adjacent to afront windshield within the vehicle to acquire a front image of thevehicle. Alternatively or in addition, the camera 310 may be disposedadjacent to a front bumper or a radiator grill.

Alternatively or in addition, the camera 310 may be disposed adjacent toa rear glass within the vehicle to acquire a rear image of the vehicle.Alternatively or in addition, the camera 310 may be disposed adjacent toa rear bumper, a trunk or a tail gate.

Alternatively or in addition, the camera 310 may be disposed adjacent toat least one of side windows within the vehicle to acquire a side imageof the vehicle. Alternatively or in addition, the camera 310 may bedisposed adjacent to a side mirror, a fender or a door.

The camera 310 may provide an acquired image to the processor 370.

The radar 320 may include electric wave transmitting and receivingportions. The radar 320 may be implemented as a pulse radar or acontinuous wave radar according to a principle of emitting electricwaves. The radar 320 may be implemented in a frequency modulatedcontinuous wave (FMCW) manner or a frequency shift keying (FSK) manneraccording to a signal waveform, among the continuous wave radar methods.

The radar 320 may detect an object in a time of flight (TOF) manner or aphase-shift manner through the medium of the electric wave, and detect aposition of the detected object, a distance from the detected object anda relative speed with the detected object.

The radar 320 may be disposed on an appropriate position outside thevehicle for detecting an object which is located at a front, rear orside of the vehicle as depicted in FIG. 2 .

The LiDAR 330 may include laser transmitting and receiving portions. TheLiDAR 330 may be implemented in a time of flight (TOF) manner or aphase-shift manner.

The LiDAR 330 may be implemented as a drive type or a non-drive type.

For the drive type, the LiDAR 330 may be rotated by a motor and detectobject near the vehicle 100.

For the non-drive type, the LiDAR 330 may detect, through lightsteering, objects which are located within a predetermined range basedon the vehicle 100. The vehicle 100 may include a plurality of non-drivetype LiDARs 330.

The LiDAR 330 may detect an object in a time of flight (TOP) manner or aphase-shift manner through the medium of a laser beam, and detect aposition of the detected object, a distance from the detected object anda relative speed with the detected object.

The LiDAR 330 may be disposed on an appropriate position outside thevehicle for detecting an object located at the front, rear or side ofthe vehicle as depicted in FIG. 2 .

The ultrasonic sensor 340 may include ultrasonic wave transmitting andreceiving portions. The ultrasonic sensor 340 may detect an object basedon an ultrasonic wave, and detect a position of the detected object, adistance from the detected object, and a relative speed with thedetected object.

The ultrasonic sensor 340 may be disposed on an appropriate positionoutside the vehicle for detecting an object located at the front, rear,or side of the vehicle.

The infrared sensor 350 may include infrared light transmitting andreceiving portions. The infrared sensor 350 may detect an object basedon infrared light, and detect a position of the detected object, adistance from the detected object, and a relative speed with thedetected object.

The infrared sensor 350 may be disposed on an appropriate positionoutside the vehicle for detecting an object located at the front, rear,or side of the vehicle.

The processor 370 may control an overall operation of each unit of theobject detecting apparatus 300.

The processor 370 may detect an object based on an acquired image, andtrack the object. The processor 370 may execute operations, such as acalculation of a distance from the object, a calculation of a relativespeed with the object and the like, through an image processingalgorithm.

The processor 370 may detect an object based on a reflectedelectromagnetic wave, which is generated when an emitted electromagneticwave is reflected from the object, and track the object. The processor370 may execute operations, such as a calculation of a distance from theobject, a calculation of a relative speed with the object, and the like,based on the reflected electromagnetic wave.

The processor 370 may detect an object based on a reflected laser beam,which is generated when an emitted laser beam is reflected from theobject, and track the object. The processor 370 may execute operations,such as a calculation of a distance from the object, a calculation of arelative speed with the object, and the like, based on the reflectedlaser beam.

The processor 370 may detect an object based on a reflected ultrasonicwave, which is generated when an emitted ultrasonic wave is reflectedfrom the object, and track the object. The processor 370 may executeoperations, such as a calculation of a distance from the object, acalculation of a relative speed with the object, and the like, based onthe reflected ultrasonic wave.

The processor may detect an object based on reflected infrared light,which is generated when emitted infrared light is reflected from theobject, and track the object. The processor 370 may execute operations,such as a calculation of a distance from the object, a calculation of arelative speed with the object, and the like, based on the reflectedinfrared light.

According to some implementations, the object detecting apparatus 300may include a plurality of processors 370 or does not include theprocessor 370. In some implementations, each of the camera 310, theradar 320, the LiDAR 330, the ultrasonic sensor 340, and the infraredsensor 350 may include a processor, respectively.

When the processor 370 is not included in the object detecting apparatus300, the object detecting apparatus 300 may operate according to thecontrol of a processor of an apparatus within the vehicle 100 or thecontroller 170.

The object detecting apparatus 300 may operate according to the controlof the controller 170.

The communication apparatus 400 is an apparatus for communicating withan external device. Here, the external device may be another vehicle, amobile terminal or a server.

The communication apparatus 400 may perform the communication byincluding at least one of a transmitting antenna, a receiving antenna,and radio frequency (RF) circuit and RF device for implementing variouscommunication protocols.

The communication apparatus 400 may include a short-range communicationunit 410, a location information unit 420, a V2X communication unit 430,an optical communication unit 440, a broadcast transceiver 450 and aprocessor 470.

According to some implementations, the communication apparatus 400 mayfurther include other components in addition to the components describedherein, or may exclude one or more of the components described herein.

The short-range communication unit 410 is a unit for facilitatingshort-range communications. Suitable technologies for implementing suchshort-range communications include Bluetooth, Radio FrequencyIDentification (RFID), Infrared Data Association (IrDA), Ultra-WideBand(UWB), ZigBee, Near Field Communication (NFC), Wireless-Fidelity(Wi-Fi), Wi-Fi Direct, Wireless USB (Wireless Universal Serial Bus), andthe like.

The short-range communication unit 410 may construct short-range areanetworks to perform short-range communication between the vehicle 100and at least one external device.

The location information unit 420 is a unit for acquiring positioninformation. For example, the location information unit 420 may includea Global Positioning System (GPS) module or a Differential GlobalPositioning System (DGPS) module.

The V2X communication unit 430 is a unit for performing wirelesscommunications with a server (Vehicle to Infra; V2I), another vehicle(Vehicle to Vehicle; V2V), or a pedestrian (Vehicle to Pedestrian; V2P).The V2X communication unit 430 may include an RF circuit implementing acommunication protocol with the infra (V2I), a communication protocolbetween the vehicles (V2V) and a communication protocol with apedestrian (V2P).

The optical communication unit 440 is a unit for communicating with anexternal device through the medium of light. The optical communicationunit 440 may include a light-emitting diode for converting an electricsignal into an optical signal and sending the optical signal to theexterior, and a photodiode for converting the received optical signalinto an electric signal.

According to some implementations, the light-emitting diode may beintegrated with lamps provided on the vehicle 100.

The broadcast transceiver 450 is a unit for receiving a broadcast signalfrom an external broadcast managing entity or transmitting a broadcastsignal to the broadcast managing entity via a broadcast channel. Thebroadcast channel may include a satellite channel, a terrestrialchannel, or both. The broadcast signal may include a TV broadcastsignal, a radio broadcast signal, and a data broadcast signal.

The processor 470 may control an overall operation of each unit of thecommunication apparatus 400.

According to some implementations, the communication apparatus 400 mayinclude a plurality of processors 470 or does not include the processor470.

When the processor 470 is not included in the communication apparatus400, the communication apparatus 400 may operate according to thecontrol of a processor of another device within the vehicle 100 or thecontroller 170.

In some implementations, the communication apparatus 400 may implement adisplay apparatus for a vehicle together with the user interfaceapparatus 200. In this instance, the display apparatus for the vehiclemay be referred to as a telematics apparatus or an Audio VideoNavigation (AVN) apparatus.

In some implementations, the communication apparatus 400 may operateaccording to the control of the controller 170.

Referring still to FIG. 7 , the driving control apparatus 500 is anapparatus for receiving a user input for driving.

In a manual mode, the vehicle 100 may be operated based on a signalprovided by the driving control apparatus 500.

The driving control apparatus 500 may include a steering input device510, an acceleration input device 530, and a brake input device 570.

The steering input device 510 may receive an input regarding a driving(proceeding) direction of the vehicle 100 from the user. The steeringinput device 510 may refer to a wheel allowing a steering input in arotating manner. According to some implementations, the steering inputdevice 510 may also refer to a touch screen, a touch pad, or a button.

The acceleration input device 530 may receive an input for acceleratingthe vehicle 100 from the user. The brake input device 570 may receive aninput for braking the vehicle 100 from the user. Each of theacceleration input device 530 and the brake input device 570 may referto a pedal. According to some implementations, the acceleration inputdevice 530 or the brake input device 570 may also refer to a touchscreen, a touch pad, or a button.

In some implementations, the driving control apparatus 500 may operateaccording to the control of the controller 170.

Referring still to FIG. 7 , the vehicle operating apparatus 600 is anapparatus for electrically controlling operations of various deviceswithin the vehicle 100.

The vehicle operating apparatus 600 may include a power train operatingunit 610, a chassis operating unit 620, a door/window operating unit630, a safety apparatus operating unit 640, a lamp operating unit 650,and an air-conditioner operating unit 660.

According to some implementations, the vehicle operating apparatus 600may further include other components in addition to the componentsdescribed, or may not include some of the components described.

In some implementations, the vehicle operating apparatus 600 may includea processor. Alternatively or in addition, each unit of the vehicleoperating apparatus 600 may individually include a processor.

The power train operating unit 610 may control an operation of a powertrain device.

The power train operating unit 610 may include a power source operatingportion 611 and a gearbox operating portion 612.

The power source operating portion 611 may perform a control for a powersource of the vehicle 100.

For example, upon using a fossil fuel-based engine as the power source,the power source operating portion 611 may perform an electronic controlfor the engine. Accordingly, an output torque and the like of the enginecan be controlled. The power source operating portion 611 may adjust theengine output torque according to the control of the controller 170.

In other example, upon using an electric energy-based motor as the powersource, the power source operating portion 611 may perform a control forthe motor. The power source operating portion 611 may adjust a rotatingspeed, a torque and the like of the motor according to the control ofthe controller 170.

The gearbox operating portion 612 may perform a control for a gearbox.

The gearbox operating portion 612 may adjust a state of the gearbox. Thegearbox operating portion 612 may change the state of the gearbox intodrive (forward) (D), reverse (R), neutral (N), or parking (P).

For example, when an engine is the power source, the gearbox operatingportion 612 may adjust a locked state of a gear in the drive (D) state.

The chassis operating unit 620 may control an operation of a chassisdevice.

The chassis operating unit 620 may include a steering operating portion621, a brake operating portion 622, and a suspension operating portion623.

The steering operating portion 621 may perform an electronic control fora steering apparatus within the vehicle 100. The steering operatingportion 621 may change a driving direction of the vehicle.

The brake operating portion 622 may perform an electronic control for abrake apparatus within the vehicle 100. For example, the brake operatingportion 622 may control an operation of brakes provided at wheels toreduce speed of the vehicle 100.

In some implementations, the brake operating portion 622 mayindividually control each of a plurality of brakes. The brake operatingportion 622 may differently control braking force applied to each of aplurality of wheels.

The suspension operating portion 623 may perform an electronic controlfor a suspension apparatus within the vehicle 100. For example, thesuspension operating portion 623 may control the suspension apparatus toreduce vibration of the vehicle 100 when a bump is present on a road.

In some implementations, the suspension operating portion 623 mayindividually control each of a plurality of suspensions.

The door/window operating unit 630 may perform an electronic control fora door apparatus or a window apparatus within the vehicle 100.

The door/window operating unit 630 may include a door operating portion631 and a window operating portion 632.

The door operating portion 631 may perform the control for the doorapparatus. The door operating portion 631 may control opening or closingof a plurality of doors of the vehicle 100. The door operating portion631 may control opening or closing of a trunk or a tail gate. The dooroperating portion 631 may control opening or closing of a sunroof.

The window operating portion 632 may perform the electronic control forthe window apparatus. The window operating portion 632 may controlopening or closing of a plurality of windows of the vehicle 100.

Referring still to FIG. 7 , the safety apparatus operating unit 640 mayperform an electronic control for various safety apparatuses within thevehicle 100.

The safety apparatus operating unit 640 may include an airbag operatingportion 641, a seatbelt operating portion 642, and a pedestrianprotecting apparatus operating portion 643.

The airbag operating portion 641 may perform an electronic control foran airbag apparatus within the vehicle 100. For example, the airbagoperating portion 641 may control the airbag to be deployed upon adetection of a risk.

The seatbelt operating portion 642 may perform an electronic control fora seatbelt apparatus within the vehicle 100. For example, the seatbeltoperating portion 642 may control passengers to be motionlessly seatedin seats 110FL, 110FR, 110RL, and 110RR (depicted in FIG. 4 ) usingseatbelts upon a detection of a risk.

The pedestrian protecting apparatus operating portion 643 may perform anelectronic control for a hood lift and a pedestrian airbag. For example,the pedestrian protecting apparatus operating portion 643 may controlthe hood lift and the pedestrian airbag to be open up upon detectingpedestrian collision.

Referring still to FIG. 7 , the lamp operating unit 650 may perform anelectronic control for various lamp apparatuses within the vehicle 100.

The air-conditioner operating unit 660 may perform an electronic controlfor an air conditioner within the vehicle 100. For example, theair-conditioner operating unit 660 may control the air conditioner tosupply cold air into the vehicle when an internal temperature of thevehicle is high.

In some implementations, the vehicle operating apparatus 600 may includea processor. Each unit of the vehicle operating apparatus 600 mayindividually include a processor.

In some implementations, the vehicle operating apparatus 600 may operateaccording to the control of the controller 170.

Referring still to FIG. 7 , the operation system 700 is a system thatcontrols various driving modes of the vehicle 100. The operation system700 may operate in an autonomous driving mode.

The operation system 700 may include a driving system 710, a parkingexit system 740, and a parking system 750.

According to implementations, the operation system 700 may furtherinclude other components in addition to the components described herein,or may exclude one or more of the components described herein.

In some implementations, the operation system 700 may include at leastone processor. Alternatively, or in addition, each unit of the operationsystem 700 may individually include at least one processor.

According to some implementations, the operation system 700 may beimplemented by the controller 170 when it is implemented in a softwareconfiguration.

In some implementations, the operation system 700 may include at leastone of the user interface apparatus 200, the object detecting apparatus300, the communication apparatus 400, the vehicle operating apparatus600, or the controller 170.

The driving system 710 may perform driving of the vehicle 100.

The driving system 710 may receive navigation information from anavigation system 770, transmit a control signal to the vehicleoperating apparatus 600, and perform driving of the vehicle 100.

The driving system 710 may receive object information from the objectdetecting apparatus 300, transmit a control signal to the vehicleoperating apparatus 600 and perform driving of the vehicle 100.

The driving system 710 may receive a signal from an external devicethrough the communication apparatus 400, transmit a control signal tothe vehicle operating apparatus 600, and perform driving of the vehicle100.

The parking exit system 740 may perform an exit of the vehicle 100 froma parking lot.

The parking exit system 740 may receive navigation information from thenavigation system 770, transmit a control signal to the vehicleoperating apparatus 600, and perform the exit of the vehicle 100 fromthe parking lot.

The parking exit system 740 may receive object information from theobject detecting apparatus 300, transmit a control signal to the vehicleoperating apparatus 600, and perform the exit of the vehicle 100 fromthe parking lot.

The parking exit system 740 may receive a signal from an external devicethrough the communication apparatus 400, transmit a control signal tothe vehicle operating apparatus 600, and perform the exit of the vehicle100 from the parking lot.

The parking system 750 may perform parking of the vehicle 100.

The parking system 750 may receive navigation information from thenavigation system 770 and transmit a control signal to the vehicleoperating apparatus 600 to park the vehicle 100.

The parking system 750 may receive object information from the objectdetecting apparatus 300, and transmit a control signal to the vehicleoperating apparatus 600 to park the vehicle 100.

The parking system 750 may receive a signal from an external devicethrough the communication apparatus 400, and transmit a control signalto the vehicle operating apparatus 600 to park the vehicle 100.

The navigation system 770 may provide navigation information. Thenavigation information may include at least one of map information,information regarding a set destination, path information according tothe set destination, information regarding various objects on a path,lane information, and current location information of the vehicle 100.

The navigation system 770 may include a memory and a processor. Thememory may store the navigation information. The processor may controlan operation of the navigation system 770.

According to some implementations, the navigation system 770 may updatestored information by receiving information from an external devicethrough the communication apparatus 400.

According to some implementations, the navigation system 770 may beclassified as a sub component of the user interface apparatus 200.

The sensing unit 120 may detect a status of the vehicle. The sensingunit 120 may include a posture sensor (e.g., a yaw sensor, a rollsensor, a pitch sensor, etc.), a collision sensor, a wheel sensor, aspeed sensor, a tilt sensor, a weight-detecting sensor, a headingsensor, a gyro sensor, a position module, a vehicle forward/backwardmovement sensor, a battery sensor, a fuel sensor, a tire sensor, asteering sensor by a turn of a handle, a vehicle internal temperaturesensor, a vehicle internal humidity sensor, an ultrasonic sensor, anillumination sensor, an accelerator position sensor, a brake pedalposition sensor, and the like.

The sensing unit 120 may acquire sensing signals with respect tovehicle-related information, such as a posture, a collision, anorientation, a position (GPS information), an angle, a speed, anacceleration, a tilt, a forward/backward movement, a battery, a fuel,tires, lamps, internal temperature, internal humidity, a rotated angleof a steering wheel, external illumination, pressure applied to anaccelerator, pressure applied to a brake pedal, and the like.

The sensing unit 120 may further include an accelerator sensor, apressure sensor, an engine speed sensor, an air flow sensor (AFS), anair temperature sensor (ATS), a water temperature sensor (WTS), athrottle position sensor (TPS), a TDC sensor, a crank angle sensor(CAS), and the like.

The interface unit 130 may serve as a path allowing the vehicle 100 tointerface with various types of external devices connected thereto. Forexample, the interface unit 130 may be provided with a port connectablewith a mobile terminal, and connected to the mobile terminal through theport. In this instance, the interface unit 130 may exchange data withthe mobile terminal.

In some implementations, the interface unit 130 may serve as a path forsupplying electric energy to the connected mobile terminal. When themobile terminal is electrically connected to the interface unit 130, theinterface unit 130 supplies electric energy supplied from a power supplyunit 190 to the mobile terminal according to the control of thecontroller 170.

The memory 140 is electrically connected to the controller 170. Thememory 140 may store basic data for units, control data for controllingoperations of units and input/output data. The memory 140 may be avariety of storage devices, such as ROM, RAM, EPROM, a flash drive, ahard drive and the like in a hardware configuration. The memory 140 maystore various data for overall operations of the vehicle 100, such asprograms for processing or controlling the controller 170.

According to some implementations, the memory 140 may be integrated withthe controller 170 or implemented as a sub component of the controller170.

The controller 170 may control an overall operation of each unit of thevehicle 100. The controller 170 may be referred to as an ElectronicControl Unit (ECU).

The power supply unit 190 may supply power required for an operation ofeach component according to the control of the controller 170.Specifically, the power supply unit 190 may receive power supplied froman internal battery of the vehicle, and the like.

At least one processor and the controller 170 included in the vehicle100 may be implemented using at least one of application specificintegrated circuits (ASICs), digital signal processors (DSPs), digitalsignal processing devices (DSPDs), programmable logic devices (PLDs),field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, and electric units performing otherfunctions.

In some implementations, the vehicle 100 according to the presentdisclosure may include a path providing device 800.

The path providing device 800 may control at least one of thosecomponents illustrated in FIG. 7 . From this perspective, the pathproviding device 800 may be the controller 170.

Without a limit to this, the path providing device 800 may be a separatedevice, independent of the controller 170. When the path providingdevice 800 is implemented as a component independent of the controller170, the path providing device 800 may be provided on a part of thevehicle 100.

Hereinafter, description will be given of implementations in which thepath providing device 800 is a component which is separate from thecontroller 170, for the sake of explanation. As such, according toimplementations described in this disclosure, the functions (operations)and control techniques described in relation to the path providingdevice 800 may be executed by the controller 170 of the vehicle. Thatis, every detail described in relation to the path providing device 800may be applied to the controller 170 in the same/similar manner.

Also, the path providing device 800 described herein may include some ofthe components illustrated in FIG. 7 and various components included inthe vehicle. For the sake of explanation, the components illustrated inFIG. 7 and the various components included in the vehicle will bedescribed with separate names and reference numbers.

Hereinafter, description will be given in more detail of a method ofautonomously driving a vehicle related to the present disclosure in anoptimized manner or providing path information optimized for the travelthe vehicle, with reference to the accompanying drawings.

FIG. 8 is a diagram of an exemplary Electronic Horizon Provider (EHP).

Referring to FIG. 8 , a path providing device 800 may autonomouslycontrol the vehicle 100 based on eHorizon (electronic Horizon).

The path providing device 800 may be an electronic horizon provider(EHP).

In some implementations, Electronic Horizon may refer to ‘ADAS Horizon’,‘ADASIS Horizon’, ‘Extended Driver Horizon’ or ‘eHorizon’.

The eHorizon may be a software, a module, or a system that performsoperations including generating vehicle's forward path information(e.g., using high-definition (HD) map data), configuring the vehicle'sforward path information based on a specified standard (protocol) (e.g.,a standard specification defined by the ADAS), and transmitting theconfigured vehicle forward path information to an application (e.g., anADAS application, a map application, etc.) which may be installed in amodule (e.g., an ECU, the controller 170, the navigation system 770,etc.) of the vehicle or in the vehicle requiring map information (orpath information).

In some implementations, the vehicle's forward path (or a path to thedestination) may be provided as a single path based on a navigation map.In some implementations, eHorizon may provide lane-based pathinformation based on a high-definition (HD) map.

Data generated by eHorizon may refer to ‘electronic horizon data’ or‘eHorizon data’.

The electronic horizon data may be driving plan data which is used togenerate a driving control signal of the vehicle 100 in a driving(traveling) system. For example, the electronic horizon data may bedriving plan data which provides a range from a point where the vehicle100 is located to horizon.

The horizon may be a point in front of a location of the vehicle 100, bya preset distance, on the basis of a preset travel path. The horizon mayrefer to a point where the vehicle 100 is to reach after a predeterminedtime from the point, at which the vehicle 100 is currently located,along a preset travel path. Here, the travel path refers to a path forthe vehicle to travel up to a final destination, and may be set by auser input.

Electronic horizon data may include horizon map data and horizon pathdata. The horizon map data may include at least one of topology data,ADAS data, HD map data, or dynamic data. According to someimplementations, the horizon map data may include a plurality of layersof data. For example, the horizon map data may include a first layerthat matches topology data, a second layer that matches ADAS data, athird layer that matches HD map data, and a fourth layer that matchesdynamic data. The horizon map data may further include static objectdata.

Topology data may be a map created by connecting road centers. Topologydata may indicate a position of a vehicle and may be in the form of dataused in a navigation for a driver. For example, topology data may beroad information excluding lane-related information. Topology data maybe generated based on data received by an infrastructure through V2I.For example, topology data may be based on data generated in theinfrastructure. By way of further example, topology data may be based ondata stored in at least one memory included in the vehicle 100.

ADAS data may refer to data related to road information. ADAS data mayinclude at least one of road slope data, road curvature data, or roadspeed limit data. ADAS data may further include no-passing zone data.ADAS data may be based on data generated in an infrastructure. In someimplementations, ADAS data may be based on data generated by the objectdetecting apparatus 300. ADAS data may be named road information data.

HD map data may include detailed lane-unit topology information of aroad, connection information of each lane, and feature information forlocalization of a vehicle (e.g., traffic signs, lane marking/attributes,road furniture, etc.). HD map data may be based on data generated in aninfrastructure.

Dynamic data may include various dynamic information that may begenerated on a road. For example, the dynamic data may includeconstruction information, variable-speed lane information, road surfacestate information, traffic information, moving object information, andany other information associated with the road. Dynamic data may bebased on data received by an infrastructure. In some implementations,dynamic data may be based on data generated by the object detectingapparatus 300.

The path providing device 800 may provide map data within a range from alocation of the vehicle 100 to the horizon. The horizon path data may bea trajectory that the vehicle 100 can take within the range from thelocation of the vehicle 100 to the horizon. The horizon path data mayinclude data indicating a relative probability to select one road at adecision point (e.g., fork, intersection, crossroads, etc.). Relativeprobability may be calculated based on a time taken to arrive at a finaldestination. For example, if a shorter time is taken to arrive at thefinal destination by selecting a first road than selecting a second roadat a decision point, the probability to select the first road may becalculated higher than the probability to select the second road.

The horizon path data may further include a main path and a sub path.The main path may be a trajectory connecting roads with a higherrelative probability to be selected. The sub path may be merged with ordiverged from at least one point on the main path. The sub path may be atrajectory connecting at least one road having a low relativeprobability to be selected at the at least one decision point on themain path.

eHorizon may be classified into categories such as software, a system,and the like. eHorizon denotes a configuration of aggregating real-timeevents, such as road shape information of a high-definition map,real-time traffic signs, road surface conditions, accidents and thelike, under a connected environment of an external server (cloudserver), V2X (Vehicle to everything) or the like, and providing theinformation related to the aggregated real-time events to the autonomousdriving system and the infotainment system.

In some implementations, eHorizon may transfer a road shape on ahigh-definition map and real-time events with respect to the front ofthe vehicle to the autonomous driving system and the infotainment systemunder an external server/V2X environment.

In order to effectively transfer eHorizon data (information) transmittedfrom eHorizon (i.e., external server) to the autonomous driving systemand the infotainment system, a data specification and transmissionmethod may be formed in accordance with a technical standard called“Advanced Driver Assistance Systems Interface Specification (ADASIS).”

The vehicle 100 may use information, which is received (generated) ineHorizon, in an autonomous driving system and/or an infotainment system.For example, the autonomous driving system may use information providedby eHorizon in safety and ECO aspects.

In terms of the safety aspect, the vehicle 100 may perform an AdvancedDriver Assistance System (ADAS) function such as Lane Keeping Assist(LKA), Traffic Jam Assist (TJA) or the like, and/or an AD (AutoDrive)function such as passing, road joining, lane change or the like, byusing road shape information and event information received fromeHorizon and surrounding object information sensed through thelocalization unit 840 provided in the vehicle.

Furthermore, in terms of the ECO aspect, the path providing device 800may receive slope information, traffic light information, and the likerelated to a forward road from eHorizon, to control the vehicle so as toget efficient engine output, thereby enhancing fuel efficiency.

The infotainment system may include convenience aspect. For example, thevehicle 100 may receive from eHorizon accident information, road surfacecondition information, and the like related to a road ahead of thevehicle, and output the received information on a display unit (e.g.,Head Up Display (HUD), CID, Cluster, etc.) provided in the vehicle, soas to provide guide information for the driver to drive the vehiclesafely.

eHorizon may receive position information related to various types ofevent information (e.g., road surface condition information,construction information, accident information, etc.) occurred on roadsand/or road-based speed limit information from the vehicle 100 or othervehicles or may collect such information from infrastructures (e.g.,measuring devices, sensing devices, cameras, etc.) installed on theroads.

In addition, the event information and the road-based speed limitinformation may be linked to map information or may be updated.

In addition, the position information related to the event informationmay be divided into lane units.

By using such information, the eHorizon system (EHP) can provideinformation necessary for the autonomous driving system and theinfotainment system to each vehicle, based on a high-definition map onwhich road conditions (or road information) can be determined on thelane basis. For example, an Electronic Horizon (eHorizon) Provider (EHP)may provide an high-definition map using coordinates of road-relatedinformation (for example, event information, position informationregarding the vehicle 100, etc.) based on a high-definition map.

The road-related information provided by the eHorizon may be informationincluded in a predetermined area (predetermined space) with respect tothe vehicle 100.

The EHP may be a component which is included in an eHorizon system andconfigured to perform functions provided by the eHorizon (or eHorizonsystem).

The path providing device 800 may be EHP, as shown in FIG. 8 .

The path providing device 800 (EHP) may receive a high-definition mapfrom an external server (or a cloud server), generate path (route)information to a destination with respect to one or more lanes of aroad, and transmit the high-definition map and the path informationgenerated with respect to the one or more lanes to a module orapplication (or program) of the vehicle requiring the map informationand the path information.

Referring to FIG. 8 , FIG. 8 illustrates an exemplary overall structureof an Electronic Horizon (eHorizon) system.

The path providing device 800 (EHP) may include a telecommunicationcontrol unit (TCU) 810 that receives a high-definition map (HD-map) froma cloud server.

The TCU 810 may be the communication apparatus 400 described above, andmay include at least one of components included in the communicationapparatus 400.

The TCU 810 may include a telematics module or a vehicle to everything(V2X) module.

The TCU 810 may receive an HD map that complies with the Navigation DataStandard (NDS) (or conforms to the NDS standard) from the cloud server.

In addition, the HD map may be updated by reflecting data sensed bysensors provided in the vehicle and/or sensors installed around road,according to the sensor ingestion interface specification (SENSORIS).

The TCU 810 may download the HD map from the cloud server through thetelematics module or the V2X module.

In addition, the path providing device 800 may include an interface unit820. In some implementations, the interface unit 820 may receive sensinginformation from one or more sensors provided in the vehicle 100.

The interface unit 820 may refer to a sensor data collector. Theinterface unit 820 may collect or receive information sensed by sensors(V.Sensors) provided in the vehicle for detecting a manipulation of thevehicle (e.g., heading, throttle, break, wheel, etc.) and sensors(S.Sensors) for detecting surrounding information of the vehicle (e.g.,Camera, Radar, LiDAR, Sonar, etc.).

The interface unit 820 may transmit the information sensed through thesensors provided in the vehicle to the TCU 810 (or processor 830) toreflect the information in the HD map.

TCU 810 may update the HD map stored in the cloud server by transmittingthe information transmitted from the interface unit 820 to the cloudserver.

The path providing device 800 may include a processor 830 (or aneHorizon module).

The processor 830 may control the TCU 810 and the interface unit 820.

The processor 830 may store the HD map received through the TCU 810, andupdate the HD map using the information received through the interfaceunit 820. This operation may be performed in a storage part of theprocessor 830.

The processor 830 may receive first path information from an audio videonavigation (AVN) or a navigation system 770.

The first path information may be route information provided inconventional systems and may be information for guiding a traveling path(travel path, driving path, driving route) to a destination. Forexample, the first path information provided by the conventional systemsprovides only one path information and does not distinguish lanes. Incontrast, when the processor 830 receives the first path information,the processor 830 may generate second path information for guiding, withrespect to one or more lanes of a road, a traveling path up to thedestination set in the first path information, by using the HD map andthe first path information. For example, the operation may be performedby a calculating part of the processor 830.

In addition, the eHorizon system may include a localization unit 840 foridentifying the position of the vehicle by using information sensedthrough the sensors (V.Sensors, S.Sensors) provided in the vehicle.

The localization unit 840 may transmit the position information of thevehicle to the processor 830 to match the position of the vehicleidentified by using the sensors provided in the vehicle with the HD map.

The processor 830 may match the position of the vehicle 100 with the HDmap based on the position information of the vehicle.

The processor 830 may generate horizon data, electronic horizon data,and horizon path data.

The processor 830 may generate the electronic horizon data by reflectingthe traveling (driving) situation of the vehicle 100. For example, theprocessor 830 may generate the electronic horizon data based ontraveling direction data and traveling speed data of the vehicle 100.

The processor 830 may merge the generated electronic horizon data withpreviously-generated electronic horizon data. For example, the processor830 may connect horizon map data generated at a first time point withhorizon map data generated at a second time point on the position basis.For example, the processor 830 may connect horizon path data generatedat a first time point with horizon path data generated at a second timepoint on the position basis.

The processor 830 may include a memory, an HD map processing part, adynamic data processing part, a matching part, and a path generatingpart.

The HD map processing part may receive HD map data from a server throughthe TCU. The HD map processing part may store the HD map data. Accordingto some implementations, the HD map processing part may also process theHD map data. The dynamic data processing part may receive dynamic datafrom the object detecting device. The dynamic data processing part mayreceive the dynamic data from a server. The dynamic data processing partmay store the dynamic data. In some implementations, the dynamic dataprocessing part may process the dynamic data.

The matching part may receive an HD map from the HD map processing part.The matching part may receive dynamic data from the dynamic dataprocessing part. The matching part may generate horizon map data bymatching the HD map data with the dynamic data.

According to some implementations, the matching part may receivetopology data. The matching part may receive ADAS data. The matchingpart may generate horizon map data by matching the topology data, theADAS data, the HD map data, and the dynamic data. The path generatingpart may generate horizon path data. The path generating part mayinclude a main path generator and a sub path generator. The main pathgenerator may generate main path data. The sub path generator maygenerate sub path data.

In addition, the eHorizon system may include a fusion unit 850 forfusing information (data) sensed through the sensors provided in thevehicle and eHorizon data generated by the eHorizon module (controlunit). For example, the fusion unit 850 may update an HD map by fusingsensing data sensed by the vehicle with an HD map corresponding toeHorizon data, and provide the updated HD map to an ADAS function, an AD(AutoDrive) function, or an ECO function.

In addition, the fusion unit 850 may provide the updated HD map to theinfotainment system.

FIG. 8 illustrates that the path providing device 800 merely includesthe TCU 810, the interface unit 820, and the processor 830, but thepresent disclosure is not limited thereto.

The path providing device 800 of the present disclosure may furtherinclude at least one of the localization unit 840 or the fusion unit850.

In addition or alternatively, the path providing device 800 (EHP) mayfurther include a navigation system 770.

With such a configuration, when at least one of the localization unit840, the fusion unit 850, or the navigation system 770 is included inthe path providing device 800 (EHP), the functions/operations/controlsperformed by the included configuration may be understood as beingperformed by the processor 830.

FIG. 9 is a block diagram of an exemplary path providing device (e.g.,the path providing device of FIG. 8 ).

The path providing device refers to a device for providing a route (orpath) to a vehicle. For example, the path providing device may be adevice mounted on a vehicle to perform communication through CANcommunication and generate messages for controlling the vehicle and/orelectric components mounted on the vehicle. By way of further example,the path providing device may be located outside the vehicle, like aserver or a communication device, and may perform communication with thevehicle through a mobile communication network. In this case, the pathproviding device may remotely control the vehicle and/or the electriccomponents mounted on the vehicle using the mobile communicationnetwork.

The path providing device 800 is provided in the vehicle, and may beimplemented as an independent device detachable from the vehicle or maybe integrally installed on the vehicle to construct a part of thevehicle 100.

Referring to FIG. 9 , the path providing device 800 may include acommunication unit (TCU) 810, an interface unit 820, and a processor830.

The communication unit 810 may be configured to perform communicationswith various components provided in the vehicle. For example, thecommunication unit 810 may receive various information provided througha controller area network (CAN).

The communication unit 810 may include a first telecommunication controlunit 812, and the first telecommunication control unit 812 may receivean HD map provided through telematics. For example, the firsttelecommunication control unit 812 may be configured to perform‘telematics communication’. The first telecommunication control unit 812performing the telematics communication may communicate with a serverand the like by using a satellite navigation system or a base stationprovided by mobile communications such as 4G or 5G.

The first telecommunication control unit 812 may communicate with atelematics communication device 910. The telematics communication device910 may include a server provided by a portal provider, a vehicleprovider, and/or a mobile communication company.

The processor 830 of the path providing device 800 may determineabsolute coordinates of road-related information (event information)based on ADAS MAP received from an external server (eHorizon) throughthe first telecommunication control unit 812. In addition, the processor830 may autonomously drive the vehicle or perform a vehicle controlusing the absolute coordinates of the road-related information (eventinformation).

The TCU 810 may include a second telecommunication control unit 814, andthe second telecommunication control unit 814 may receive various typesof information provided through vehicle to everything (V2X)communication. For example, the second telecommunication control unit814 may be configured to perform ‘V2X communication’. The V2Xcommunication may be a technology of exchanging or sharing information,such as traffic condition and the like, while communicating with roadinfrastructures and other vehicles during driving.

The second telecommunication control unit 814 may communicate with a V2Xcommunication device 930. The V2X communication device 930 may include ato mobile terminal associated with a pedestrian or a person riding abike, a fixed terminal installed on a road, another vehicle, and thelike.

Here, the another vehicle may denote at least one of vehicles existingwithin a predetermined distance from the vehicle 100 or vehiclesapproaching by a predetermined distance or shorter with respect to thevehicle 100.

The present disclosure may not be limited thereto, and the anothervehicle may include all the vehicles capable of performing communicationwith the TCU 810. According to this specification, for the sake ofexplanation, an example will be described in which the another vehicleis at least one vehicle existing within a predetermined distance fromthe vehicle 100 or at least one vehicle approaching by a predetermineddistance or shorter with respect to the vehicle 100.

The predetermined distance may be determined based on a distance capableof performing communication through the TCU 810, determined according toa specification of a product, or determined/varied based on a user'ssetting or V2X communication standard.

The second telecommunication control unit 814 may be configured toreceive LDM data from another vehicle. The LDM data may be a V2X message(BSM, CAM, DENM, etc.) transmitted and received between vehicles throughV2X communication. The LDM data may include position information relatedto the another vehicle.

The processor 830 may determine a position of the vehicle 100 relativeto the another vehicle, based on the position information related to thevehicle 100 and the position information related to the another vehicleincluded in the LDM data received through the second telecommunicationcontrol unit 814.

In addition, the LDM data may include speed information regardinganother vehicle. The processor 830 may also determine a relative speedof the another vehicle using speed information of the vehicle 100 andthe speed information of the another vehicle. The speed information ofthe vehicle 100 may be calculated using a degree to which the locationinformation of the vehicle received through the TCU 810 changes overtime or calculated based on information received from the drivingcontrol apparatus 500 or the power train operating unit 610 of thevehicle 100.

The second telecommunication control unit 814 may be the V2Xcommunication unit 430 described above.

If the TCU 810 is a component that performs communication with a devicelocated outside the vehicle 100 using wireless communication, theinterface unit 820 may be a component performing communication with adevice located inside the vehicle 100 using wired or wirelesscommunication.

The interface unit 820 may receive information related to driving of thevehicle from most of electric components provided in the vehicle 100.Information transmitted from the electric component provided in thevehicle to the path providing device 800 is referred to as ‘vehicledriving information (or vehicle travel information)’. For example, whenthe electric component is a sensor, the vehicle driving information maybe sensing information sensed by the sensor.

Vehicle driving information may include vehicle information andsurrounding information related to the vehicle. Information related tothe inside of the vehicle with respect to a frame of the vehicle may bedefined as the vehicle information, and information related to theoutside of the vehicle may be defined as the surrounding information.

The vehicle information refers to information related to the vehicleitself. For example, the vehicle information may include a travelingspeed, a traveling direction, an acceleration, an angular velocity, alocation (GPS), a weight, a number of passengers on board the vehicle, abraking force of the vehicle, a maximum braking force, air pressure ofeach wheel, a centrifugal force applied to the vehicle, a driving (ortravel) mode of the vehicle (autonomous driving mode or manual drivingmode), a parking mode of the vehicle (autonomous parking mode, automaticparking mode, manual parking mode), whether or not a user is on boardthe vehicle, and information associated with the user.

The surrounding information refers to information related to anotherobject located within a predetermined range around the vehicle, andinformation related to the outside of the vehicle. The surroundinginformation of the vehicle may be a state of a road surface on which thevehicle is traveling (e.g., a frictional force), the weather, a distancefrom a preceding (or following) vehicle, a relative speed of a preceding(or following) vehicle, a curvature of a curve when a driving lane isthe curve, information associated with an object existing in a referenceregion (predetermined region) based on the vehicle, whether or not anobject enters (or leaves) the predetermined region, whether or not theuser exists near the vehicle, information associated with the user (forexample, whether or not the user is an authenticated user), and thelike.

The surrounding information may also include ambient brightness,temperature, a position of the sun, information related to a nearbysubject (a person, another vehicle, a sign, etc.), a type of a drivingroad surface, a landmark, line information, and driving laneinformation, and information required for an autonomousdriving/autonomous parking/automatic parking/manual parking mode.

In addition, the surrounding information may further include a distancefrom an object existing around the vehicle to the vehicle, collisionpossibility, a type of an object, a parking space for the vehicle, anobject for identifying the parking space (e.g., a parking line, astring, another vehicle, a wall, etc.), and the like.

The vehicle driving information is not limited to the example describedabove and may include all information generated from the componentsprovided in the vehicle.

In some implementations, the processor 830 may be configured to controlone or more electric components provided in the vehicle using theinterface unit 820.

For example, the processor 830 may determine whether or not at least oneof a plurality of preset or predetermined conditions is satisfied, basedon vehicle driving information received through the TCU 810. Based on asatisfied condition, the processor 830 may control the one or moreelectric components in different ways.

In connection with the preset conditions, the processor 830 may detectan occurrence of an event in an electric component provided in thevehicle and/or application, and determine whether the detected eventmeets a preset condition. At this time, the processor 830 may alsodetect the occurrence of the event from information received through theTCU 810.

The application may be implemented, for example, as a widget, a homelauncher, and the like, and may refer to various types of programs thatcan be executed on the vehicle. Accordingly, the application may be aprogram that performs various functions, such as a web browser, a videoplayback, message transmission/reception, schedule management, orapplication update.

In addition, the application may include at least one of forwardcollision warning (FCW), blind spot detection (BSD), lane departurewarning (LDW), pedestrian detection (PD), Curve Speed Warning (CSW), orturn-by-turn navigation (TBT). For example, the occurrence of the eventmay be a missed call, presence of an application to be updated, amessage arrival, start on, start off, autonomous travel on/off, pressingof an LCD awake key, an alarm, an incoming call, a missed notification,and the like.

In some implementations, the occurrence of the event may be a generationof an alert set in the advanced driver assistance system (ADAS), or anexecution of a function set in the ADAS. For example, the occurrence ofthe event may be an occurrence of forward collision warning, anoccurrence of blind spot detection, an occurrence of lane departurewarning, an occurrence of lane keeping assist warning, or an executionof autonomous emergency braking.

In some implementations, the occurrence of the event may also be achange from a forward gear to a reverse gear, an occurrence of anacceleration greater than a predetermined value, an occurrence of adeceleration greater than a predetermined value, a change of a powerdevice from an internal combustion engine to a motor, or a change fromthe motor to the internal combustion engine.

In addition, even when various electronic control units (ECUs) providedin the vehicle perform specific functions, it may be determined as theoccurrence of the events. For example, when a generated event satisfiesthe preset condition, the processor 830 may control the interface unit820 to display information corresponding to the satisfied condition onone or more displays provided in the vehicle.

FIG. 10 is a diagram of an exemplary eHorizon.

Referring to FIG. 10 , the path providing device 800 may autonomouslydrive the vehicle 100 based on the eHorizon.

eHorizon may be classified into categories such as software, a system,and the like. The eHorizon denotes a configuration in which road shapeinformation on a detailed map under a connected environment of anexternal server (cloud), V2X (Vehicle to everything) or the like andreal-time events such as real-time traffic signs, road surfaceconditions, accidents and the like are merged to provide relevantinformation to autonomous driving systems and infotainment systems. Foran example, eHorizon may refer to an external server (a cloud or a cloudserver). By way of further example, eHorizon may transfer a road shapeon a high-definition map and real-time events with respect to the frontof the vehicle to the autonomous driving system and the infotainmentsystem under an external server/V2X environment.

In order to effectively transfer eHorizon data (information) transmittedfrom eHorizon (i.e., external server) to the autonomous driving systemand the infotainment system, a data specification and transmissionmethod may be formed in accordance with a technical standard called“Advanced Driver Assistance Systems Interface Specification (ADASIS).”

The path providing device 800 may use information, which is receivedfrom eHorizon, in the autonomous driving system and/or the infotainmentsystem. For example, the autonomous driving system may be divided into asafety aspect and an ECO aspect.

In terms of the safety aspect, the vehicle 100 may perform an AdvancedDriver Assistance System (ADAS) function such as Lane Keeping Assist(LKA), Traffic Jam Assist (TJA) or the like, and/or an AD (AutoDrive)function such as passing, road joining, lane change or the like, byusing road shape information and event information received fromeHorizon and surrounding object information sensed through thelocalization unit 840 provided in the vehicle 100.

Furthermore, in terms of the ECO aspect, the path providing device 800may receive slope information, traffic light information, and the likerelated to a forward road from eHorizon, to control the vehicle so as toget efficient engine output, thereby enhancing fuel efficiency.

The infotainment system may include convenience aspect. For example, thevehicle 100 may receive from eHorizon accident information, road surfacecondition information, and the like related to a road ahead of thevehicle and output the received information on a display unit (forexample, Head Up Display (HUD), CID, Cluster, etc.) provided in thevehicle, so as to provide guide information for the driver to drive thevehicle safely.

Referring to FIG. 10 , the eHorizon (external server) may receivelocation information related to various types of event information(e.g., road surface condition information 1010 a, constructioninformation 1010 b, accident information 1010 c, etc.) occurred on roadsand/or road-based speed limit information 1010 d from the vehicle 100 orother vehicles 1020 a and 1020 b or may collect such information frominfrastructures (e.g., measuring devices, sensing devices, cameras,etc.) installed on the roads.

Furthermore, the event information and the road-based speed limitinformation may be linked to map information or may be updated.

In addition, the location information related to the event informationmay be divided with respect to one or more lanes of a road.

By using such information, the eHorizon (external server) can provideinformation necessary for the autonomous driving system and theinfotainment system to each vehicle, based on a high-definition mapcapable of determining a road situation (or road information) withrespect to one or more lanes of the road. For example, the eHorizon(external server) may provide a high-definition map using coordinates ofroad-related information (for example, event information, positioninformation regarding the vehicle 100, etc.) based on a high-definitionmap.

The road-related information provided by the eHorizon may be informationcorresponding to a predetermined region (predetermined space) withrespect to the vehicle 100.

In some implementations, the path providing device 800 may acquireposition information related to another vehicle through communicationwith the another vehicle. Communication with the another vehicle may beperformed through V2X (Vehicle to everything) communication, and datatransmitted/received to/from the another vehicle through the V2Xcommunication may be data in a format defined by a Local Dynamic Map(LDM) standard.

The LDM denotes a conceptual data storage located in a vehicle controlunit (or ITS station) including information related to a safe and normaloperation of an application (or application program) provided in avehicle (or an intelligent transport system (ITS)). The LDM may, forexample, comply with EN standards.

The LDM differs from the foregoing ADAS MAP in the data format andtransmission method. For an example, the ADAS MAP may correspond to ahigh-definition map having absolute coordinates received from eHorizon(external server), and the LDM may denote a high-definition map havingrelative coordinates based on data transmitted and received through V2Xcommunication.

The LDM data (or LDM information) denotes data mutually transmitted andreceived through V2X communication (vehicle to everything) (e.g., V2V(Vehicle to Vehicle) communication, V2I (Vehicle to Infra)communication, or V2P (Vehicle to Pedestrian) communication).

The LDM may be implemented, for example, by a storage for storing datatransmitted and received through V2X communication, and the LDM may beformed (stored) in a vehicle control device provided in each vehicle.

The LDM data (or LDM information) denotes data mutually transmitted andreceived through V2X communication (vehicle to everything) (e.g., V2V(Vehicle to Vehicle) communication, V2I (Vehicle to Infra)communication, or V2P (Vehicle to Pedestrian) communication). The LDMdata may include a Basic Safety Message (BSM), a Cooperative AwarenessMessage (CAM), and a Decentralized Environmental Notification message(DENM), and the like, for example. For example, the LDM data may referto a V2X message or an LDM message.

The vehicle control device may efficiently manage LDM data (or V2Xmessages) transmitted and received between vehicles using the LDM.

Based on LDM data received via V2X communication, the LDM may store,distribute to another vehicle, and continuously update all relevantinformation (e.g., a location, a speed, a traffic light status, weatherinformation, a road surface condition, and the like of the vehicle(another vehicle)) related to a traffic situation around a place wherethe vehicle is currently located (or a road situation for an area withina predetermined distance from a place where the vehicle is currentlylocated).

For example, a V2X application provided in the path providing device 800registers in the LDM, and receives a specific message such as all theDENMs in addition to a warning about a failed vehicle. Then, the LDM mayautomatically assign the received information to the V2X application,and the V2X application may control the vehicle based on the informationassigned from the LDM.

As described above, the vehicle 100 may be controlled by using the LDMformed by the LDM data collected through V2X communication.

The LDM may provide road-related information to the vehicle controldevice. The road-related information provided by the LDM provides only arelative distance and a relative speed with respect to another vehicle(or an event generation point), other than map information havingabsolute coordinates. For example, the vehicle 100 may performautonomous driving using an ADAS MAP (absolute coordinates HD map)according to the ADASIS standard provided by eHorizon, but the map maybe used only to determine a road condition in a surrounding area of thevehicle.

In addition, the vehicle 100 may perform autonomous driving using an LDM(relative coordinates HD map) formed by LDM data received through V2Xcommunication, but there is a limitation in that accuracy is inferiordue to insufficient absolute position information.

The path providing device 800 included in the vehicle 100 may generate afused definition map using the ADAS MAP received from the eHorizon andthe LDM data received through the V2X communication, and control(autonomously drive) the vehicle in an optimized manner using the fuseddefinition map.

FIG. 11A illustrates an example of a data format of LDM data (or LDM)transmitted and received between vehicles via V2X communication, andFIG. 11B illustrates an example of a data format of an ADAS MAP receivedfrom an external server (eHorizon).

Referring to FIG. 11A, the LDM data (or LDM) 1050 may be formed to havefour layers of data.

The LDM data 1050 may include a first layer 1052, a second layer 1054, athird layer 1056 and a fourth layer 1058.

The first layer 1052 may include static information, for example, mapinformation, among road-related information.

The second layer 1054 may include landmark information (e.g., specificplace information specified by a maker among a plurality of placeinformation included in the map information) among informationassociated with roads. The landmark information may include locationinformation, name information, size information, and the like.

The third layer 1056 may include traffic situation related information(e.g., traffic light information, construction information, accidentinformation, etc.) among information associated with roads. Theconstruction information and the accident information may includeposition information.

The fourth layer 1058 may include dynamic information (e.g., objectinformation, pedestrian information, other vehicle information, etc.)among the road-related information. The object information, pedestrianinformation, and other vehicle information may include locationinformation.

For example, the LDM data 1050 may include information sensed through asensing unit of another vehicle or information sensed through a sensingunit of the vehicle of the present disclosure, and may includeroad-related information that is transformed in real time as it goesfrom the first layer to the fourth layer.

Referring to FIG. 11B, the ADAS MAP may be formed to have four layers ofdata similar to the LDM data.

The ADAS MAP 1060 may denote data received from eHorizon and formed toconform to the ADASIS specification.

The ADAS MAP 1060 may include a first layer 1062, a second layer 1064, athird layer 1066, and a fourth layer 1068.

The first layer 1062 may include topology information. The topologyinformation, for example, is information that explicitly defines aspatial relationship, and may indicate map information.

The second layer 1064 may include landmark information (e.g., specificplace information specified by a maker among a plurality of placeinformation included in the map information) among informationassociated with the road. The landmark information may include positioninformation, name information, size information, and the like.

The third layer 1066 may include high-definition map information. Thehigh-definition map information may be referred to as an HD-MAP, androad-related information (e.g., traffic light information, constructioninformation, accident information) may be recorded in the lane unit. Theconstruction information and the accident information may includelocation information.

The fourth layer 1068 may include dynamic information (e.g., objectinformation, pedestrian information, other vehicle information, etc.).The object information, pedestrian information, and other vehicleinformation may include location information.

For example, the ADAS MAP 1060 may include road-related information thatis transformed in real time as it goes from the first layer to thefourth layer, similarly to the LDM data 1050.

The processor 830 may autonomously drive the vehicle 100. For example,the processor 830 may autonomously drive the vehicle 100 based onvehicle driving information sensed through various electric componentsprovided in the vehicle 100 and information received through the TCU810.

More specifically, the processor 830 may control the TCU 810 to acquirethe position information of the vehicle. For example, the processor 830may acquire the position information (location coordinates) of thevehicle 100 through the location information unit 420 of the TCU 810.

Furthermore, the processor 830 may control the first telecommunicationcontrol unit 812 of the TCU 810 to receive map information from anexternal server. Here, the first telecommunication control unit 812 mayreceive ADAS MAP from the external server (eHorizon). The mapinformation may be included in the ADAS MAP.

In addition, the processor 830 may control the second telecommunicationcontrol unit 814 of the TCU 810 to receive position information ofanother vehicle from the another vehicle. Here, the secondtelecommunication control unit 814 may receive LDM data from the anothervehicle. The position information of the another vehicle may be includedin the LDM data.

The another vehicle denotes a vehicle existing within a predetermineddistance from the vehicle 100, and the predetermined distance may be acommunication-available distance of the TCU 810 or a distance set by auser.

The processor 830 may control the communication unit to receive the mapinformation from the external server and the position information of theanother vehicle from the another vehicle.

Furthermore, the processor 830 may fuse the acquired positioninformation of the vehicle and the received position information of theanother vehicle into the received map information, and control thevehicle 100 based on at least one of the fused map information orvehicle-related information sensed through the sensing unit 120.

Here, the map information received from the external server may denotehighly detailed map information (HD-MAP) included in the ADAS MAP. TheHD map information may be recorded with road-related information withrespect to one or more lanes of a road.

The processor 830 may fuse the position information of the vehicle 100and the position information of the another vehicle into the mapinformation with respect to one or more lanes of a road. In addition,the processor 830 may fuse the road-related information received fromthe external server and the road-related information received from theanother vehicle into the map information with respect to one or morelanes of a road.

The processor 830 may generate ADAS MAP required for the control of thevehicle using the ADAS MAP received from the external server and thevehicle-related information received through the sensing unit 120. Morespecifically, the processor 830 may apply the vehicle-relatedinformation sensed within a predetermined range through the sensing unit120 to the map information received from the external server. Here, thepredetermined range may be an available distance which can be sensed byan electric component provided in the vehicle 100 or may be a distanceset by a user.

The processor 830 may control the vehicle by applying thevehicle-related information sensed within the predetermined rangethrough the sensing unit to the map information and then additionallyfusing the location information of the another vehicle thereto. Forexample, when the vehicle-related information sensed within thepredetermined range through the sensing unit is applied to the mapinformation, the processor 830 may only use the information within thepredetermined range from the vehicle, and thus a range capable ofcontrolling the vehicle may be local.

However, the position information of the another vehicle receivedthrough the V2X module may be received from the another vehicle locatedout of the predetermined range. It may be because thecommunication-available distance of the V2X module communicating withthe another vehicle through the V2X module is farther than apredetermined range of the sensing unit 120.

As a result, the processor 830 may fuse the location information of theanother vehicle included in the LDM data received through the secondtelecommunication control unit 814 into the map information on which thevehicle-related information has been sensed, so as to acquire thelocation information of the another vehicle located in a broader rangeand more effectively control the vehicle using the acquired information.For example, it is assumed that a plurality of other vehicles is crowdedahead in a lane in which the vehicle 100 travels, and it is also assumedthat the sensing unit can sense only location information related to theimmediately preceding vehicle. In this case, when only vehicle-relatedinformation sensed within a predetermined range on map information isused, the processor 830 may generate a control command to control thevehicle such that the vehicle overtakes the preceding vehicle.

However, a plurality of other vehicles may be actually present ahead,which may make the vehicle difficult to overtake the other vehicles. Atthis time, the vehicle 100 may acquire the location information ofanother vehicle received through the V2X module. Here, the receivedlocation information of the another vehicle may include locationinformation related to not only the vehicle immediately in front of thevehicle 100 (or the preceding vehicle) but also a plurality of othervehicles in front of the preceding vehicle.

The processor 830 may additionally fuse the location information relatedto the plurality of other vehicles acquired through the V2X module intomap information to which the vehicle-related information is applied, soas to determine a situation where it is inappropriate to overtake thepreceding vehicle.

With such configuration, the vehicle 100 can overcome the technicallimitation associated with conventional systems that onlyvehicle-related information acquired through the sensing unit 120 ismerely fused to high-definition map information and thus autonomousdriving is enabled only within a predetermined range. For example,vehicle 100 can achieve more accurate and stable vehicle control byadditionally fusing information related to other vehicles (e.g., speeds,locations of other vehicles), which have been received from the othervehicles located at a farther distance than the predetermined rangethrough the V2X module, as well as vehicle-related information sensedthrough the sensing unit, into map information.

Vehicle control described herein may include at least one ofautonomously driving the vehicle 100 or outputting a warning messageassociated with the driving of the vehicle.

Hereinafter, description will be given in more detail of a method inwhich a processor controls a vehicle using LDM data received through aV2X module, ADAS MAP received from an external server (eHorizon), andvehicle-related information sensed through a sensing unit provided inthe vehicle, with reference to the accompanying drawings.

FIGS. 12A and 12B are exemplary views illustrating a method in which acommunication device receives high-definition map data.

The server may divide HD map data into tile units and provide them tothe path providing device 800. The processor 830 may receive HD map datain the tile units from the server or another vehicle through the TCU810. Hereinafter, HD map data received in tile units is referred to as‘HD map tile’.

The HD map data is divided into tiles having a predetermined shape, andeach tile corresponds to a different portion of the map. By connectingall the tiles, the full HD map data may be acquired. Since the HD mapdata has a high capacity, the vehicle 100 may be provided with ahigh-capacity memory in order to download and use the full HD map data.As communication technologies are developed, it is more efficient todownload, use, and delete HD map data in tile units, rather than toprovide the high-capacity memory in the vehicle 100.

For the convenience of description, a case in which the predeterminedshape is rectangular is described as an example, but the predeterminedshape may be modified to various polygonal shapes.

The processor 830 may store the downloaded HD map tile in the memory140. The processor 830 may delete the stored HD map tile. For example,the processor 830 may delete the HD map tile when the vehicle 100 leavesan area corresponding to the HD map tile. By way of further example, theprocessor 830 may delete the HD map tile when a preset time elapsesafter storage.

As illustrated in FIG. 12A, when there is no preset destination, theprocessor 830 may receive a first HD map tile 1251 including a location(position) 1250 of the vehicle 100. The server receives data of thelocation 1250 of the vehicle 100 from the vehicle 100, and transmits thefirst HD map tile 1251 including the location 1250 of the vehicle 100 tothe vehicle 100. In addition, the processor 830 may receive HD map tiles1252, 1253, 1254, and 1255 around the first HD map tile 1251. Forexample, the processor 830 may receive the HD map tiles 1252, 1253,1254, and 1255 that are adjacent to top, bottom, left, and right sidesof the first HD map tile 1251, respectively. In this case, the processor830 may receive a total of five HD map tiles. For example, the processor830 may further receive HD map tiles located in a diagonal direction,together with the HD map tiles 1252, 1253, 1254, and 1255 adjacent tothe top, bottom, left, and right sides of the first HD map tile 1251. Inthis case, the processor 830 may receive a total of nine HD map tiles.

As illustrated in FIG. 12B, when there is a preset destination, theprocessor 830 may receive tiles associated with a path from the location1250 of the vehicle 100 to the destination. The processor 830 mayreceive a plurality of tiles to cover the path.

In some implementations, the processor 830 may receive all the tilescovering the path at one time.

Alternatively, the processor 830 may receive the entire tiles in adividing manner while the vehicle 100 travels along the path. Forexample, the processor 830 may receive only some of the entire tilesbased on the location of the vehicle 100 while the vehicle 100 travelsalong the path. Thereafter, the processor 830 may continuously receivetiles during the travel of the vehicle 100 and delete the previouslyreceived tiles.

The processor 830 may generate electronic horizon data based on the HDmap data.

The vehicle 100 may travel in a state where a final destination is set.The final destination may be set based on a user input received via theuser interface apparatus 200 or the communication apparatus 400.According to some implementations, the final destination may be set bythe driving system 710.

In the state where the final destination is set, the vehicle 100 may belocated within a preset distance from a first point during driving. Whenthe vehicle 100 is located within the preset distance from the firstpoint, the processor 830 may generate electronic horizon data having thefirst point as a start point and a second point as an end point. Thefirst point and the second point may be points on the path heading tothe final destination. The first point may be described as a point wherethe vehicle 100 is located or will be located in the near future. Thesecond point may be described as the horizon described above.

The processor 830 may receive an HD map of an area including a sectionfrom the first point to the second point. For example, the processor 830may request an HD map for an area within a predetermined radial distancefrom the section between the first point and the second point andreceive the requested HD map.

The processor 830 may generate electronic horizon data for the areaincluding the section from the first point to the second point, based onthe HD map. The processor 830 may generate horizon map data for the areaincluding the section from the first point to the second point. Theprocessor 830 may generate horizon path data for the area including thesection from the first point to the second point. The processor 830 maygenerate a main path for the area including the section from the firstpoint to the second point. The processor 830 may generate data of a subpath for the area including the section from the first point to thesecond point.

When the vehicle 100 is located within a preset distance from the secondpoint, the processor 830 may generate electronic horizon data having thesecond point as a start point and a third point as an end point. Thesecond point and the third point may be points on the path heading tothe final destination. The second point may be described as a pointwhere the vehicle 100 is located or will be located in the near future.The third point may be described as the horizon described above. In someimplementations, the electronic horizon data having the second point asthe start point and the third point as the end point may begeographically connected to the electronic horizon data having the firstpoint as the start point and the second point as the end point.

The operation of generating the electronic horizon data using the secondpoint as the start point and the third point as the end point may beperformed by correspondingly applying the operation of generating theelectronic horizon data having the first point as the start point andthe second point as the end point.

According to some implementations, the vehicle 100 may travel even whenthe final destination is not set.

FIG. 13 is a flowchart of an exemplary path providing method of the pathproviding device of FIG. 9 .

The processor 830 may receive a high-definition map from an externalserver. Specifically, the processor 830 may receive map information (HDmap, high-definition map) including a plurality of layers of data from aserver (external server, cloud server) (S1310).

The external server is an example of the telematics communication device910 as a device capable of communicating through the firsttelecommunication control unit 812. The high-definition map is composedof a plurality of layers of data. Furthermore, the high-definition mapmay include at least one of the four layers described above with respectto FIG. 11B as an ADAS MAP.

The map information may include horizon map data described above. Thehorizon map data may refer to an ADAS MAP (or LDM MAP) or HD MAP dataincluding a plurality of layers of data while satisfying the ADASISstandard described with respect to FIG. 11B.

In addition, the processor 830 of the path providing device 800 mayreceive sensing information from one or more sensors provided in thevehicle (S1320). The sensing information may refer to information sensedby each sensor (or information processed after being sensed). Thesensing information may include various information according to thetypes of data that can be sensed by the sensor.

The processor 830 may identify any one lane in which the vehicle 100 islocated on a road composed of a plurality of lanes, based on an image(or video) received from an image sensor among sensing information(S1330). Here, the lane may refer to a lane in which the vehicle 100currently equipped with the path providing device 800 is driving.

The processor 830 may determine a lane in which the vehicle 100 equippedwith the path providing device 800 is driving by using (analyzing) animage (or video) received from an image sensor (or camera) among thesensors.

In addition, the processor 830 may estimate an optimal path that isexpected or planned to move the vehicle 100 based on the identified lanein units of lanes using map information (S1340). Here, the optimal pathmay refer to the foregoing horizon path data or main path describedabove. However, the present disclosure is not limited thereto, and theoptimal path may further include a sub path. Here, the optimal path maybe referred to as a Most Preferred Path or Most Probable Path, and maybe abbreviated as MPP.

For example, the processor 830 may predict or plan an optimal path inwhich the vehicle 100 can travel to a destination based on a specificlane in which the vehicle 100 is driving, using map information.

The processor 830 may generate autonomous driving visibility informationin which sensing information is fused with the optimal path to transmitit to at least one of electrical parts provided in a server or a vehicle(S1350).

Here, the autonomous driving visibility information may refer toelectronic horizon information (or electronic horizon data) describedabove. The autonomous driving visibility information (or data,environment) used by the vehicle 100 to perform autonomous driving inunits of lanes, may denote environmental data for autonomous driving inwhich all information (map information, vehicles, objects, movingobjects, environment, weather, etc.) within a predetermined range aremerged based on a road or an optimal path including a path in which thevehicle 100 moves, as illustrated in FIG. 10 . The autonomous drivingenvironment data may refer to data (or overall data environment) basedon which the processor 830 of the vehicle 100 autonomously drives thevehicle 100 or calculates an optimal path of the vehicle 100.

In some implementations, the other hand, the autonomous drivingvisibility information may denote information for guiding a driving pathin units of lanes. This is information in which at least one of sensinginformation or dynamic information is merged into an optimal path, andfinally, may be information for guiding a driving path in units oflanes.

When autonomous driving visibility information refers to information forguiding a driving path in units of lanes, the processor 830 may generatedifferent autonomous driving visibility information according to whethera destination is set in the vehicle 100.

For example, when the destination is set in the vehicle 100, theprocessor 830 may generate autonomous driving visibility information forguiding a driving path (travel path) to the destination in units oflanes.

By way of further example, when no destination is set in the vehicle100, the processor 830 may calculate a main path (most preferred path,MPP) having the highest possibility that the vehicle 100 may drive, andgenerate autonomous driving visibility information for guiding the mainpath (MPP) in units of lanes. In this case, the autonomous drivingvisibility information may further include sub path information on subpaths branched from the most preferred path (MPP) for the vehicle 100 tobe movable at a higher probability than a predetermined reference.

The autonomous driving visibility information may provide a driving pathto the destination for each lane indicated on a road, thereby providingmore precise and detailed path information. The autonomous drivingvisibility information may be path information conforming to thestandard of ADASIS v3.

The processor 830 may merge dynamic information for guiding a movableobject located on an optimal path with the autonomous driving visibilityinformation, and update the optimal path based on the dynamicinformation (S1360). The dynamic information may be included in mapinformation received from a server, and may be information included inany one (e.g., a fourth layer 1068) of a plurality of layers of data.

The electric component provided in the vehicle may be at least one ofvarious components provided in the vehicle, and may include, forexample, a sensor, a lamp, and the like. The electric component providedin the vehicle may be referred to as an eHorizon Receiver (EHR) in termsof receiving an ADASIS message including autonomous driving visibilityinformation from the processor 830.

The processor 830 according to the present disclosure may be referred toas an eHorizon Provider (EHP) in terms of providing (transmitting) anADASIS Message including autonomous driving visibility information.

The ADASIS message including the autonomous driving visibilityinformation may be a message in which the autonomous driving visibilityinformation is converted to comply with the ADASIS standardspecification.

The foregoing description will be summarized as follows.

The processor 830 may generate autonomous driving visibility informationfor guiding a road located in the front of the vehicle in units of lanesusing the high-definition map.

The processor 830 may receive sensing information from one or moresensors provided in the vehicle 100 through the interface unit 820. Thesensing information may be vehicle driving information.

The processor 830 may identify any one lane in which the vehicle islocated on a road made up of a plurality of lanes based on an imagereceived from an image sensor among the sensing information. Forexample, when the vehicle 100 is driving in a first lane on a 8-laneroad, the processor 830 may identify the first lane as a lane in whichthe vehicle 100 is located based on the image received from the imagesensor.

The processor 830 may estimate an optimal path that is expected orplanned to move the vehicle 100 based on the identified lane in units oflanes using the map information.

Here, the optimal path may refer to a Most Preferred Path or MostProbable Path, and may be abbreviated as MPP.

The vehicle 100 may drives autonomously along the optimal path. Whendriving manually, the vehicle 100 may provide navigation informationthat guides the optimal path to the driver.

The processor 830 may generate autonomous driving visibilityinformation, in which the sensing information is merged into the optimalpath. The autonomous driving visibility information may be referred toas “eHorizon” or “electronic horizon” or “electronic horizon data” or an“ADASIS message” or a “field-of-view information tree graph.”

The processor 830 may use the autonomous driving visibility informationdifferently depending on whether a destination has been set in thevehicle 100.

For example, when the destination is set in the vehicle 100, theprocessor 830 may generate an optimal path for guiding a driving path tothe destination in units of lanes using the autonomous drivingvisibility information.

By way of further example, when a destination has not been set in thevehicle 100, the processor 830 may calculate a main path in which thevehicle 100 is most likely to drive in units of lanes using theautonomous driving visibility information. In this case, the autonomousdriving visibility information may further include sub path informationon sub paths branched from the most preferred path (MPP) for the vehicle100 to be movable at a higher probability than a predeterminedreference.

The autonomous driving visibility information may provide a driving pathto the destination for each lane indicated on a road, thereby providingmore precise and detailed path information. The path information may bepath information conforming to the standard of ADASIS v3.

The autonomous driving visibility information may be provided bysubdividing a path in which the vehicle must drive or a path in whichthe vehicle can drive in units of lanes. The autonomous drivingvisibility information may include information for guiding a drivingpath to a destination in units of lanes. When the autonomous drivingvisibility information is displayed on a display mounted on the vehicle100, guide lines for guiding lanes that can be driven on a map andinformation within a predetermined range (e.g., roads, landmarks, othervehicles, surrounding objects, weather information, etc.) based on thevehicle may be displayed. Moreover, a graphic object indicating thelocation of the vehicle 100 may be included in at least one lane onwhich the vehicle 100 is located among a plurality of lanes included inthe map.

The autonomous driving visibility information may be fused with dynamicinformation for guiding a movable object located on the optimal path.The dynamic information may be received by the processor 830 through thecommunication unit 810 and/or the interface unit 820, and the processor830 may update the optimal path based on the dynamic information. As theoptimal path is updated, the autonomous driving visibility informationis also updated.

The dynamic information may include dynamic data.

The processor 830 may provide the autonomous driving visibilityinformation to at least one electric component provided in the vehicle.Moreover, the processor 830 may provide the autonomous drivingvisibility information to various applications installed in the systemof the vehicle 100.

The electric component refers to any device mounted on the vehicle 100and capable of performing communication, and may include the componentsdescribed above with reference to FIGS. 1 through 9 (e.g., thecomponents 120-700 described above with reference to FIG. 7 ). Forexample, an object detecting apparatus 300 such as a radar and a lidar,a navigation system 770, a vehicle operating apparatus 600, and the likemay be included in the electric components.

In addition, the electric component may further include an applicationexecutable in the processor 830 or a module that executes theapplication.

The electric component may perform its own function to be carried outbased on the autonomous driving visibility information.

The autonomous driving visibility information may include a path inunits of lanes and a location of the vehicle 100, and may includedynamic information including at least one object that must be sensed bythe electric component. The electric component may reallocate a resourceto sense an object corresponding to the dynamic information, determinewhether the dynamic information matches sensing information sensed byitself, or change a setting value for generating sensing information.

The autonomous driving visibility information may include a plurality oflayers, and the processor 830 may selectively transmit at least one ofthe layers according to an electric component that receives theautonomous driving visibility information.

Specifically, the processor 830 may select at least one of a pluralityof layers included in the autonomous driving visibility information,based on at least one of a function being executed by the electricalcomponent or a function scheduled to be executed. In addition, theprocessor 830 may transmit the selected layer to the electroniccomponent, but the unselected layer may not be transmitted to theelectrical component.

The processor 830 may receive external information generated by anexternal device from the external device located within a predeterminedrange with respect to the vehicle.

The predetermined range is a distance at which the secondtelecommunication control unit 814 can perform communication, and mayvary according to the performance of the second telecommunicationcontrol unit 814. When the second telecommunication control unit 814performs V2X communication, a V2X communication range may be defined asthe predetermined range.

Moreover, the predetermined range may vary according to an absolutespeed of the vehicle 100 and/or a relative speed with respect to theexternal device.

The processor 830 may determine the predetermined range based on theabsolute speed of the vehicle 100 and/or the relative speed with respectto the external device, and allow communication with an external devicelocated within the determined predetermined range.

Specifically, external devices capable of communicating through thesecond telecommunication control unit 814 may be classified into a firstgroup or a second group based on the absolute speed of the vehicle 100and/or the relative speed with respect to the external device. Externalinformation received from an external device included in the first groupis used to generate dynamic information described below, but externalinformation received from an external device included in the secondgroup is not used to generate the dynamic information. Even whenexternal information is received from an external device included in thesecond group, the processor 830 may ignore the external information.

The processor 830 may generate dynamic information of an object thatmust be sensed by at least one electrical part provided in the vehiclebased on the external information, and may match the dynamic informationto the field-of-view information for autonomous driving.

For example, the dynamic information may correspond to the fourth layerdescribed above with reference to FIGS. 11A and 11B.

As described above with respect to FIGS. 11A and 11B, the path providingdevice 800 may receive the ADAS MAP and/or the LDM data. Specifically,the path providing device 800 may receive the ADAS MAP from thetelematics communication device 910 through the first telecommunicationcontrol unit 812, and the LDM data from the V2X communication device 930through the second telecommunication control unit 814.

The ADAS MAP and the LDM data may be composed of a plurality of layersof data each having the same format. The processor 830 may select atleast one layer from the ADAS MAP, select at least one layer from theLDM data, and generate the autonomous driving visibility informationincluding the selected layers.

For example, the processor 830 may select the first to third layers ofthe ADAS MAP, select the fourth layer of the LDM data, and generate oneautonomous driving visibility information by aligning those four layersinto one. In this case, the processor 830 may transmit a reject messagefor rejecting the transmission of the fourth layer to the telematicscommunication device 910. This is because receiving partial informationexcluding the fourth layer uses less resources of the firsttelecommunication control unit 812 than receiving all informationincluding the fourth layer. By matching part of the ADAS MAP with partof the LDM data, complementary information can be utilized.

In some implementations, the processor 830 may select the first tofourth layers of the ADAS MAP, select the fourth layer of the LDM data,and generate one autonomous driving visibility information may begenerated by aligning those five layers into one. In this case, prioritymay be given to the fourth layer of the LDM data. When there isdiscrepancy information that does not match the fourth layer of the LDMdata in the fourth layer of the ADAS MAP, the processor 830 may deletethe discrepancy information or correct the discrepancy information basedon the LDM data.

The dynamic information may be object information for guiding apredetermined object. For example, at least one of a location coordinatefor guiding the location of the predetermined object, and informationfor guiding the shape, size, and type of the predetermined object may beincluded in the dynamic information.

The predetermined object may denote an object that obstructs driving inthe corresponding lane among objects that can drive on a road.

For example, the predetermined object may include a bus stopping at abus stop, a taxi stopping at a taxi stop, a truck dropping a courier,and the like.

By way of further example, the predetermined object may include agarbage collection vehicle driving at a constant speed or below, or alarge vehicle (e.g., truck or container truck, etc.) determined toobstruct view.

As another example, the predetermined object may include an objectindicating an accident, road damage, or construction.

As described above, the predetermined object may include all types ofobjects disallowing the driving of the present vehicle 100 orobstructing the lane not to allow the vehicle 100 to drive. Trafficsignals such as ice roads, pedestrians, other vehicles, constructionsigns, and traffic lights to be avoided by the vehicle 100 maycorrespond to the predetermined object and may be received by the pathproviding device 800 as the external information.

Meanwhile, the processor 830 may determine whether a predeterminedobject guided by the external information is located within a referencerange based on the driving path of the vehicle 100.

Whether or not the predetermined object is located within the referencerange may vary depending on the lane on which the vehicle 100 drives andthe location of the predetermined object.

For example, external information for guiding a sign indicating theconstruction of a third lane ahead 1 km while driving on a first lanemay be received. When the reference range is set to 1 m with respect tothe vehicle 100, the sign is located out of the reference range. It isbecause when the vehicle 100 continues to drive on the first lane, thethird lane is located out of 1 m with respect to the vehicle 100. On thecontrary, when the reference range is set to 10 m with respect to thevehicle 100, the sign is located within the reference range.

The processor 830 may generate the dynamic information based on theexternal information when the predetermined object is located within thereference range, but does not generate the dynamic information when thepredetermined object is located out of the reference range. In otherwords, the dynamic information may be generated only when thepredetermined object guided by the external information is located on adriving path of the vehicle 100 or within a reference range capable ofaffecting the driving path of the vehicle 100.

Since the path providing device combines information received throughthe first communication module and information received through thesecond communication module into one, which may result in generating andproviding optimal autonomous driving visibility information capable ofcomplementing different types of information provided through suchdifferent communication modules. This is because information receivedthrough the first communication module cannot reflect information inreal time but such limitation can be complemented by informationreceived through the second communication module.

Further, since when there is information received through the secondcommunication module, the processor 830 controls the first communicationmodule so as not to receive the corresponding information, it may bepossible to use the bandwidth of the first telecommunication controlunit less than the related art. In other words, the resource use of thefirst telecommunication control unit may be minimized.

Hereinafter, a path providing device which can include at least one ofthose components described above, and a method of controlling the samewill be described in more detail with reference to the accompanyingdrawings.

FIGS. 14A and 14B are conceptual views illustrating exemplary types ofsensors of a vehicle that are used in a path providing device, and FIG.15 is a conceptual view illustrating an exemplary path providing deviceusing a plurality of sensor data.

The path providing device 800 may generate/update autonomous drivingvisibility information or an optimal path by using at least one sensorprovided in the vehicle.

The at least one sensor provided in the vehicle may mean all sensorsincluded in the sensing unit 120 of the vehicle described above.

Specifically, the at least one sensor provided in the vehicle mayinclude vehicle sensors (V. sensors) that sense the operations of thevehicle itself (e.g., a heading direction of the vehicle, a steeringangle, speed, whether a brake operates, whether an accelerationoperates, whether a lamp is lighted on, etc.), and safety sensors (S.Sensors) (e.g., a camera, LiDAR, radar, an ultrasonic sensor, anultra-wideband (UWB) sensors, etc.).

In addition, in terms of sensing information related to driving ofanother vehicle from the another vehicle through V2X communication ofthe communication unit 810, the communication unit 810 (or the V2Xmodule of the communication unit) may also be understood to be includedin the category of the sensor.

Referring to FIG. 14A, the sensors described herein are mainly safetysensors (camera, LIDAR, radar, ultrasonic sensor, ultra-wideband (UWB)sensor, etc.) that sense surrounding information of the vehicle.However, it should be noticed that the present disclosure is not limitedthereto.

Radar (Radar Detection and Ranging) may be mainly used to sense speed ofa moving object using radio waves. As illustrated in FIG. 14A, the radarmay have the longest sensing range, and may sense an object locatedfarthest from the vehicle.

In some implementations, LIDAR (Light Imaging Detection and Ranging) maydetect an object using laser.

Since the LIDAR uses a short frequency, it can detect even smallobjects, and generate accurate 3D monochrome images. However, the LIDARmay be limited in use at night and in cloudy weather.

The radar can easily operate even in cloudy weather and at night.However, the radar, compared to the LIDAR, may have difficulties withdetecting small objects and does not provide precise images of objects.

As illustrated in FIG. 14A, since the radar has a narrow viewing anglebut a long sensing range, it can be mainly used for an adaptive cruisecontrol (ACC) function among advanced driver assistant system (ADAS)functions.

In addition, although the LIDAR has a shorter sensing range than theradar, since it has a wider viewing angle than the radar and canaccurately detect even small objects, it can be mainly used foremergency braking, pedestrian detection, and collision avoidancefunctions, among the ADAS functions.

As illustrated in FIG. 14A, a camera among the sensors of the vehiclethat can be used in the path providing device 800 has a shorter sensingrange compared to the radar and the LIDAR, but may be configured to havea wider viewing angle.

The camera may capture a space around the vehicle as an image (or video)through an image sensor. Since the camera directly captures(photographs) the space, it is possible to sense text, pictures, etc.placed on a plane. Accordingly, the camera may be used for variousfunctions, such as traffic sign recognition, lane departure warning,surround view, and parking assistance, among the ADAS functions.

In addition, the radar may also be used for additional functions, suchas cross traffic alert, blind spot detection, and rear collisionwarning.

In addition, the ultrasonic sensor may be mainly used for a parkingassistance function.

As illustrated in FIG. 14A, a plurality of sensors provided in thevehicle 100 usable in the path providing device 800 may have differentsensing ranges, respectively, and may have different advantages.

Accordingly, the path providing device 800, as illustrated in FIG. 14B,can generate/update autonomous driving visibility information or anoptimal path in an optimized manner, by various combinations of theplurality of sensors having the different sensing ranges.

For example, the processor 830 may limitedly receive only dynamicinformation within a range having a predetermined width from an optimalpath through the communication unit 810.

At this time, as illustrated in FIG. 14B, the path providing device 800may additionally sense information by using the plurality of sensorshaving the different sensing ranges, and update the autonomous drivingvisibility information and the optimal path using the sensedinformation.

The sensors may sense various information on areas each having a widthwider than the range having the predetermined width (or areas out of therange having the predetermined width), and their sensing ranges may varydepending on types of sensors, as illustrated in FIG. 14A.

Hereinafter, one implementations of a path providing device 800 using aplurality of sensors will be described.

As illustrated in FIG. 15 , a path providing device 800 may include acommunication unit 810 that receives a high-definition (HD) map and adynamic map (or dynamic information) from an external server 1400, amemory that stores the received high-definition map and dynamic map, anda localization module that fuses a current position (location) of thevehicle with the high-definition map.

In addition, to fuse a plurality of sensor data, the path providingdevice 800 may include a sensor interface 1510 that receives sensor datafrom the sensors (e.g., camera, radar, LIDAR, V2X module, etc.) providedin the vehicle, and a sensor fusion unit 1520 that fuses the receivedplurality of sensor data.

A function of fusing a plurality of sensor data will be referred to as asensor fusion function.

The processor 830 may receive map information (high-definition map(HD-map) and dynamic map) from the server 1400 through the communicationunit 810 and calculate (or determine) path (route) information on themap data based on destination information of the vehicle.

The destination information of the vehicle, for example, may bedetermined by a user input.

The path information may include an optimal path indicating a path alongwhich the vehicle should travel in units of lanes described above.

The processor 830 may transmit map information including the pathinformation to the sensor fusion unit 1520.

In some implementations, a plurality of sensor information may be inputto the sensor fusion unit 1520 through the sensor interface 1510. Theinput sensor information may be information that raw data sensed bysensors is processed to be available by sensors (or the sensor interface1510).

The sensor fusion unit 1520 may fuse path information and sensorinformation to generate autonomous driving visibility information(electronic horizon information) in which map information and sensorinformation are fused with each other.

Thereafter, the sensor fusion unit 1520 may broadcast the autonomousdriving visibility information through a network.

The sensor fusion unit 1520 may transmit the autonomous drivingvisibility information, in which the sensor information has been fused,to an electric component or electric part 1500 (e.g., a sensor, a lamp,an application, etc.) provided in the vehicle, so that the sensorinformation can be selectively used according to situations.

The sensor fusion unit 1520 may appropriately fuse (merge and integrate)a plurality of sensor data according to a situation, generate meaningfulinformation, and fuse it with path information.

The operation/function/control method of the sensor fusion unit 1520described above may be performed by the processor 830.

FIG. 15 exemplarily illustrates that the sensor fusion unit 1520 isseparately provided, for convenience of description, but the presentdisclosure is not limited thereto.

Upon receiving sensor information from a plurality of sensors throughthe sensor interface 1510 (which can also be performed by the processor830), the processor 830 may generate autonomous driving visibilityinformation by fusing the sensor information with path information, andtransmit the generated autonomous driving visibility information toelectric components provided in the vehicle.

In addition, the processor 830 may generate meaningful information byfusing (merging, integrating) a plurality of sensor data, and fuse themeaningful information with the path information.

For the convenience of description, the sensor fusion unit 1520 will beomitted, and the processor 830 will be described as performing thesensor fusion function.

The processor 830 may fuse map information with sensor information toconstruct an environment model (i.e., autonomous driving visibilityinformation) that includes short-range object information near thevehicle (e.g., short-range object information determined based on thesensor information), and long-range map information (long-range mapinformation included in the map information).

Hereinafter, with reference to the accompanying drawings, descriptionwill be given in more detail of a method of generating optimizedautonomous driving visibility information and optimal path by fusingsensor information sensed by a plurality of sensors with mapinformation.

FIG. 16 is a flowchart illustrating an exemplary control method, andFIG. 17 is a conceptual view illustrating the control method illustratedin FIG. 16 .

As described above, the path providing device 800 may receive sensinginformation from one or more sensors provided in the vehicle through aninterface.

The processor 830 may specify one lane in which the vehicle 100 islocated on a road having a plurality of lanes based on images, whichhave been received from an image sensor, among the sensing information.

The processor 830 may estimate an optimal path, in which the vehicle 100is expected or planned to move based on the specified lane, in laneunits using the map information.

The processor 830 may generate autonomous driving visibility informationby fusing the sensing information with the optimal path. The autonomousdriving visibility information may be fused with dynamic information (ordynamic map) guiding a movable object located on the optimal path andupdate the optimal path based on the dynamic information.

At this time, the processor 830 may receive different types of sensordata from a plurality of sensors provided in the vehicle (S1610).

The processor 830 may update at least one of autonomous drivingvisibility information and an optimal path by using informationgenerated by combining at least two types of sensor data (the pluralityof sensor data) (S1620).

Specifically, the processor 830 may receive different types of sensordata from a plurality of sensors. For example, the processor 830 mayreceive an image from a camera and receive distance information to aspecific object from a radar.

The processor 830 may generate information by combining the receivedplurality of sensor data. Here, the information generated by combiningthe plurality of sensor data may include information on differentattributes of an object or information on a plurality of objects ofdifferent types.

For example, the processor 830 may generate/update the autonomousdriving visibility information using a plurality of sensor data receivedfrom a plurality of sensors.

As illustrated in FIG. 17 , the processor 830 may determine a type of anobject located at the front of the vehicle 100 through an image receivedfrom a camera.

In addition, the processor 830 may sense information related to adistance up to the object located in front of the vehicle and a volumeof the object, based on sensor data received from a LIDAR or radar.

In addition, the processor 830 may receive information related toanother vehicle (e.g., type, speed, deceleration/acceleration, volume,path information, optimal path in lane units, etc. which are all relatedto the another vehicle), on the basis of information received from theanother vehicle through V2X communication.

As described above, the processor 830 may generate autonomous drivingvisibility information by fusing the plurality of sensor data receivedthrough the plurality of sensors, thereby enhancing reliability andaccuracy of the autonomous driving visibility information.

In some implementations, the present disclosure can determine an optimalcombination of sensors in consideration of forward road information(e.g., road properties, curved degree, slope, dynamic information,etc.), on which the vehicle should travel, and characteristics of therespective sensors.

Hereinafter, description will be given in more detail of an exemplarymethod of determining types of a plurality of sensors to be used togenerate/update autonomous driving visibility information or an optimalpath, with reference to the accompanying drawings.

FIGS. 18 to 21 are flowcharts and conceptual views illustrating anexemplary method of updating autonomous driving visibility informationand an optimal path using a plurality of sensor data.

Referring to FIG. 18 , the processor 830 may divide an optimal path intoa plurality of sections according to characteristics of the optimal path(characteristics of roads or external environmental conditions) (S1810).

Specifically, when the optimal path has been set based on autonomousdriving visibility information, the processor 8130 may determinecharacteristics of roads including (passing through) the optimal path byanalyzing map information.

In addition, the processor 830 may receive external environmentalconditions (road material, weather, brightness, visibility, etc.) ofeach region, through which the optimal path passes, from the server 1400through the communication unit 810.

The processor 830 may determine a plurality of sensors to be used ineach section based on a characteristic set for each section (S1820).

Also, the processor 830 may update the autonomous driving visibilityinformation using sensor data sensed by the determined sensors (S1830).

Specifically, the processor 830 may determine sections set to use aplurality of sensors based on a type of sensor to be used for eachsection.

Subsequently, the processor 830 may update the autonomous drivingvisibility information by fusing the plurality of sensor data acquiredthrough the plurality of sensors, in response to the vehicle's arrivalat the determined section.

For example, the characteristic (i.e., the road characteristic) may bedetermined based on at least one of a road shape and time.

In addition, referring to FIG. 14B, the processor 830 may updateautonomous driving visibility information according to a situation,using information, which is included in a predetermined range set basedon an optimal path in map information (i.e., dynamic informationincluded in map information), and information generated by combining ormerging the at least two types of sensor data.

In order to select a plurality of sensor data, the path providing devicemay divide a road, on which the vehicle is to travel, into a pluralityof sections based on an optimal path generated by the processor 830.

For example, as illustrated in FIG. 19 , the processor 830 may divide anoptimal path into a plurality of sections (first to fourth sections)according to characteristics.

For example, the first section has a characteristic of a straight roadin bright weather. Accordingly, a camera may be set to be used in thefirst section since the camera exhibits high accuracy.

The second section has a characteristic of a curved section.Accordingly, a sensor (e.g., a radar) having straightness in a curvedsection may have a disadvantage of a very short sensing distance, whichmay make it impossible to recognize a situation after the curve.

Accordingly, in the second section, the processor 830 may obtain laneinformation and speed information in advance through an HD map, so as toincrease a recognition rate of the camera.

The processor 830 may also change an angle of the camera by recognizingthe curve in the second section.

The third section has a characteristics of a tunnel. Accordingly, sinceit has a dark environment, the field of view (visibility) of the camerais significantly lowered. Accordingly, in the third section, theprocessor 830 may adjust an amount of light of a headlamp or a lightirradiation direction to secure the visibility of the camera sensor. Inaddition, the processor 830 may set a radar or LIDAR sensor to be usedin the third section.

The fourth section has a characteristic of heavy rain. The processor 830may receive external status information (weather information, etc.) inthe fourth section through the communication unit 810, and determinethat it is raining heavily in the fourth section based on the receivedinformation.

In the fourth section, the processor 830 may decrease relativeimportance of sensors (e.g., a camera) whose recognition ratedeteriorates due to the weather, and increase relative importance ofsensors (e.g., a LIDAR) that are less affected by the weather.

For example, in the fourth section, the processor 830 may update theautonomous driving visibility information using sensor data obtainedthrough the radar and ultrasonic sensor, without using informationreceived through the camera.

As described above, the processor 830 may divide a region in which thevehicle is to be driven into a plurality of sections based on an optimalpath, decide sensors to be used in each section in advance, and acquiresensor data using sensors to be used in an arrived section when thevehicle arrives in each section.

The processor 830 may then update the autonomous driving viewinformation using the acquired sensor data.

That is, the path providing device 800 may generate a time table forsensor fusion according to a path map passing through an optimal path,and perform a sensor fusion based on the time table.

In some implementations, the processor 830 may determine sensors thatcan sense currently-required information among the plurality of sensorsprovided in the vehicle, on the basis of map information. Thereafter,the processor 830 may receive at least two types of sensor data from thedetermined sensors.

When the processor 830 receives the at least two types of sensor data,the processor 830 may process the received sensor data to generateinformation necessary for a situation that the vehicle is currentlyfacing.

The processor 830 may also update the autonomous driving visibilityinformation by adding the generated information to the map information.

For example, when the vehicle is currently located at an intersection,it may be necessary to acquire a type of object located at a center ofthe intersection and information related to a distance and volume to andof the object.

The processor 830 may determine sensors that are capable of sensingcurrently-required information (a type of an object existing at anintersection, a distance to the object, and a volume of the object, inorder to prevent collision at the intersection), on the basis of the mapinformation.

For example, the processor 830 may determine a camera capable ofdetermining a type of object, and a radar and LIDAR capable of sensingdistance and volume to and of the object.

The processor 830 may receive at least two types of sensor data from thedetermined sensors, and process the received sensor data to generateinformation (the type of the object, the distance to the object, and thevolume of the object) that is required for a situation that the vehicleis currently facing.

The processor 830 may also update the autonomous driving visibilityinformation by adding the generated information to the map information.

In addition, the processor 830 may transmit information generated byfusing at least two types of sensor data to the server 1400 through thecommunication unit 810 so that the generated information is shared withother vehicles.

As described above, the processor 830 may recognize differentcharacteristics of a specific object using a plurality of sensor data.

The processor 830 may determine a type of a specific object throughfirst sensor data, and determine a distance to the specific object and avolume of the specific object through second sensor data.

For example, the sensor may include a camera.

The processor 830 may merge object information received through thecamera with map information, and update autonomous driving visibilityinformation using a type of an object included in the objectinformation.

By way of further example, the sensor may include at least one of aradar and a LIDAR.

The processor 830 may sense information related to the distance to theobject and the volume of the object through at least one of the radarand the LIDAR, and correct (modify) the object information (informationrelated to the specific object) included in the map information.

In this way, the processor 830 may determine (recognize) differentattributes or properties (type, distance, volume) of a specific objectby fusing a plurality of sensor data.

In some implementations, the processor 830 may fuse a plurality ofsensor data sensed through at least two sensors based on at least one ofa driving speed of the vehicle, a shape of a road (a straight road, acurved road, or a slope of a road), time, or an external environmentstate (e.g., weather, brightness, or visibility), and update an optimalpath using the fused data.

Specifically, the processor 830 may load information on a type of asensor to be used for each external environment state and information ona type of a sensor to be used for each road shape from a memory, or mayreceive the same through the communication unit 810.

The information may be linked with a type of a sensor which is optimizedfor use for each external environment state.

For example, the information may be linked with the use of the radar andthe ultrasonic sensor, other than the camera, in an external environmentstate in which it is raining.

Further, it is indicated in the information that the radar and thecamera having long sensing distances are used in a straight road, andthe LIDAR having a relatively short sensing distance is used in a curvedroad.

The processor 830 may receive a plurality of sensor data throughdifferent types of sensors, based on information related to a type of asensor to be used for each external environment state and informationrelated to a type of a sensor to be used for each road shape.

Thereafter, the processor 830 may receive a plurality of sensor datathrough different sensors based on at least one of an externalenvironment state and a shape of a road on which the vehicle is driving.

Afterwards, the processor 830 may then update autonomous drivingvisibility information by selectively combining the received pluralityof sensor data.

For example, the processor 830 may receive a plurality of sensor datafrom a plurality of sensors, including the camera, the radar, the LIDAR,and the ultrasonic sensor, based on the external environment state, andthe shape of the road on the vehicle is moving, as described above,

Thereafter, the processor 830 may update autonomous driving visibilityinformation by selectively combining the received plurality of sensordata.

For example, in a situation where the vehicle is currently moving on astraight road and the visibility is not significantly lowered althoughit is raining, the processor 830 may update autonomous drivingvisibility information by selectively combining sensor data sensedthrough the radar and an image received through the camera.

In some implementations, the present disclosure can not only combine(merge, fuse) sensor data using a plurality of sensors provided in thevehicle, but also additionally combine (fuse) information received fromanother vehicle through V2X communication.

Referring to FIG. 20 , the processor 830 may receive V2X informationfrom another vehicle through the communication unit 810 (S2010).

The V2X information received from the another vehicle is informationrelated to the another vehicle and may include information related to adriving speed of the another vehicle, a type of the another vehicle, adriving lane of the another vehicle, a position of the another vehicle,a path (or optimal path) set in the another vehicle, a size of theanother vehicle, and any information associated with the anothervehicle.

The processor 830 may predict an event which has occurred (or is tooccur) on the optimal path, by using autonomous driving visibilityinformation, object information (e.g., type of the object, a distancefrom the vehicle to the object, or a volume of the object) which isgenerated by fusing a plurality sensor data received through a pluralityof sensors, and the information (V2X information) received from anothervehicle through the communication unit 810 (S2020).

For example, as illustrated in FIG. 21 , the processor 830 may set onlyinformation related to a lane and a driving path for turning right at anintersection when the turning right at the intersection has been set inthe optimal path included in the autonomous driving visibilityinformation.

At this time, the processor 830 may update the autonomous drivingvisibility information by fusing the object information obtained throughthe plurality of sensors and the V2X information received from theanother vehicle.

For example, the processor 830 may recognize a pedestrian based on theobject information received through the camera and determine a distanceto the object (the pedestrian) using the radar and the LIDAR.

In addition, the processor 830 may receive the V2X information and graspthe information related to the another vehicle which is moving at anintersection.

Accordingly, the processor 830 may identify an event to occur at theintersection (i.e., to occur on the optimal path) based on those typesof information. For example, the processor 830 may predict a collisionwith a pedestrian or a collision with another vehicle when driving alongthe optimal path set in the autonomous driving visibility information.

In this case, the processor 830 may perform an autonomous drivingcontrol for the vehicle based on the prediction. For example, theprocessor 830 may stop the vehicle or decelerate the driving speed ofthe vehicle until the pedestrian enters an area in which the pedestriandoes not interfere with driving, or until the another vehicle passes.

With this configuration, the present disclosure can provide a controlmethod capable of updating autonomous driving visibility information oran optimal path or controlling a vehicle to allow more stable autonomousdriving of the vehicle by additionally using V2X information receivedfrom another vehicle as well as a plurality of sensor data.

In some implementations, according to the present disclosure, a methodof fusing a plurality of sensor data may be controlled differentlyaccording to a sensing range.

FIG. 22 is a flowchart illustrating an exemplary method of fusing aplurality of sensor data and updating an optimal path according tosensing ranges of sensors in a path providing device.

Referring to FIG. 22 , the processor 830 may fuse sensor data indifferent ways according to a sensing range of each of a plurality ofsensors (S2210).

Specifically, as illustrated in FIG. 14A, a first sensor (for example,the camera) among a plurality of sensors may have a sensing range of afirst radius based on the vehicle.

Further, a second sensor (for example, the radar) among the plurality ofsensors may have a sensing range of a second radius longer than thefirst radius based on the vehicle.

The processor 830 may fuse sensor data sensed by the first sensor andsensor data sensed by the second sensor up to the first radius, andupdate an optimal path (or autonomous driving visibility information)using the fused data. (S2220).

In some implementations, the processor 830 may update the optimal path(or autonomous driving visibility information) using only the sensordata of the second sensor in a section between the first radius and thesecond radius (S2230).

In the first radius, since sensing by both the first sensor and thesecond sensor is allowed, the autonomous driving visibility informationor the optimal path can be updated by using the plurality of sensor datasensed by the first sensor and the second sensor (e.g., the camera andthe radar).

In some implementations, between the first radius and the second radius,since sensing by the first sensor (the camera) is impossible, theautonomous driving visibility information or the optimal path can beupdated using only the sensor data of the second sensor (the radar)which can sense up to the second radius.

The same can be applied to a case where three or more sensors havedifferent sensing ranges.

For example, when a first sensor is capable of sensing up to a firstradius, a second sensor is capable of sensing up to a second radiusfarther than the first radius, and a third sensor is capable of sensingup to a third radius farther than the second radius, the processor 830may update autonomous driving visibility information or an optimal pathby using all of the first to third sensors up to the first radius, onlythe second and third sensors at a section between the first radius andthe second radius, and only the third sensor at a section between thesecond radius and the third radius.

As described above, the present disclosure can provide a new controlmethod capable of differently controlling a sensor combination methodaccording to a sensing range of each sensor.

In this specification, updating autonomous driving visibilityinformation may be understood as a concept including even updating anoptimal path.

Hereinafter, effects of a path providing device and a path providingmethod thereof according to the present disclosure will be described.

First, the present disclosure can provide a path providing device thatis optimized for generating or updating autonomous driving visibilityinformation.

Second, the present disclosure can perform update more accurately byupdating autonomous driving visibility information or an optimal pathusing a plurality of sensor data.

Third, the present disclosure can perform optimized update using aplurality of sensor data required according to situations.

Fourth, the present disclosure can provide a new path providing device,capable of updating autonomous driving visibility information or anoptimal path by using a different method of fusing a plurality of sensordata depending on a sensing range of each sensor, and a path providingmethod thereof.

The present disclosure can be implemented as computer-readable codes(applications or software) in a program-recorded medium. The method ofcontrolling the autonomous vehicle can be realized by a code stored in amemory or the like.

The computer-readable medium may include all types of recording deviceseach storing data readable by a computer system. Examples of suchcomputer-readable media may include hard disk drive (HDD), solid statedisk (SSD), silicon disk drive (SDD), ROM, RAM, CD-ROM, magnetic tape,floppy disk, optical data storage element and the like. Also, thecomputer-readable medium may also be implemented as a format of carrierwave (e.g., transmission via an Internet). The computer may include theprocessor or the controller. Therefore, it should also be understoodthat the above-described embodiments are not limited by any of thedetails of the foregoing description, unless otherwise specified, butrather should be construed broadly within its scope as defined in theappended claims, Therefore, all changes and modifications that fallwithin the metes and bounds of the claims, or equivalents of such metesand bounds are therefore intended to be embraced by the appended claims.

What is claimed is:
 1. A path providing device configured to provide apath information to a vehicle, the device comprising: a communicationunit, configured to receive, from a server, map information including aplurality of layers of data; and a processor configured to: identify alane in which the vehicle is located among a plurality of lanes of aroad based on sensing information received from one or more sensorsdisposed at the vehicle and including an image received from an imagesensor, determine an optimal path for guiding the vehicle from theidentified lane, the optimal path comprising one or more lanes includedin the map information, generate autonomous driving visibilityinformation and transmit the generated autonomous driving visibilityinformation to at least one of the server or an electric componentdisposed at the vehicle based on the sensing information and thedetermined optimal path, to thereby cause the vehicle to performautonomous driving according to the autonomous driving visibilityinformation, and update the optimal path based on dynamic informationrelated to a movable object located on the optimal path and theautonomous driving visibility information, wherein the processor isconfigured to receive different types of sensor data from a plurality ofsensors disposed at the vehicle, and update at least one of theautonomous driving visibility information or the optimal path based oninformation generated by combining at least two types of sensor data,wherein the processor is configured to fuse sensor data in a differentmanner according to a sensing range of each of the plurality of sensors,wherein a first sensor of the plurality of sensors has a sensing rangeof a first radius based on the vehicle, wherein a second sensor of theplurality of sensors has a sensing range of a second radius, the secondradius being longer than the first radius from a location of thevehicle, and wherein the processor is configured to: fuse sensor datasensed by the first sensor and the second sensor up to the first radiusto update the optimal path using the fused sensor data, and update theoptimal path only using sensor data of the second sensor in a sectionbetween the first radius and the second radius.
 2. The device of claim1, wherein the processor is configured to: divide the optimal path intoa plurality of sections according to characteristics of the optimalpath, determine one or more sensors to be used, among the plurality ofsensors, in each section based on a characteristic associated with eachof the plurality of sections, and update the autonomous drivingvisibility information based on sensor data sensed by the determined oneor more sensors.
 3. The device of claim 2, wherein the processor isconfigured to: determine a section set to use the determined one or moresensors based on a type of each of the determined one or more sensors,and update the autonomous driving visibility information by fusing aplurality of sensor data acquired by the one or more sensors, based onan arrival at the determined section.
 4. The device of claim 2, whereinthe characteristic is determined based on at least one of a road shapeor time of the day.
 5. The device of claim 1, wherein the processor isconfigured to update the autonomous driving visibility informationaccording to situations, using (i) information included within apredetermined range set based on the optimal path in the map informationand (ii) information generated by fusing the at least two types ofsensor data.
 6. The device of claim 1, wherein the processor isconfigured to: Determine one or more sensors that can sensecurrently-required information among the plurality of sensors based onthe map information, and receive the at least two types of sensor datafrom the determined one or more sensors.
 7. The device of claim 6,wherein the processor is configured to: generate information necessaryfor a situation that the vehicle is currently facing, by processing thereceived sensor data, based on the at least two types of sensor databeing received, and update the autonomous driving visibility informationby adding the generated information to the map information.
 8. Thedevice of claim 1, wherein the processor is configured to recognizedifferent characteristics of a specific object using a plurality ofsensor data.
 9. The device of claim 8, wherein the processor isconfigured to: determine a type of the specific object based on firstsensor data of the plurality of sensor data, and determine a distance upto the specific object and a volume of the specific object based onsecond sensor data of the plurality of sensor data.
 10. The device ofclaim 8, wherein the plurality of sensors includes a camera, and whereinthe processor is configured to merge object information received throughthe camera with the map information, and update the autonomous drivingvisibility information using a type of the specific object included inthe object information.
 11. The device of claim 8, wherein the pluralityof sensors includes at least one of a radar or a LIDAR, and wherein theprocessor is configured to sense information related to a distance tothe specific object and a volume of the specific object through the atleast one of the radar or the LIDAR, and correct object informationincluded in the map information using the sensed information related tothe distance and the volume.
 12. The device of claim 1, wherein theprocessor is configured to: fuse a plurality of sensor data sensedthrough at least two sensors based on at least one of a driving speed ofthe vehicle, a road shape, time of the day, or an external environmentstate, and update the optimal path based on the fused data.
 13. Thedevice of claim 1, wherein the processor is configured to receive aplurality of sensor data through different sensors, based on informationrelated to a type of sensor to be used for each external environmentstate and a type of sensor to be used for each road shape.
 14. Thedevice of claim 13, wherein the processor is configured to: receive theplurality of sensor data through different sensors based on at least oneof the external environment state or a shape of a road providing theidentified lane and on which the vehicle is currently located, andselectively merge the received plurality of sensor data to update theautonomous driving visibility information.
 15. The device of claim 1,wherein the processor is configured to predict an event to occur on theoptimal path based on (i) the autonomous driving visibility information,(ii) object information generated by merging a plurality of sensor datareceived through the plurality of sensors, and (iii) informationreceived from another vehicle through the communication unit.
 16. A pathproviding method, performed by a path providing device configured toprovide path information to a vehicle, the method comprising: receiving,from a server, map information including a plurality of layers of data;receiving, from one or more sensors disposed at the vehicle, sensinginformation including an image received from an image sensor;identifying a lane in which the vehicle is located among a plurality oflanes of a road based on the sensing information; determining an optimalpath for guiding the vehicle from the identified lane, the optimal pathcomprising one or more lanes included in the map information; generatingautonomous driving visibility information and transmitting the generatedautonomous driving visibility information to at least one of the serveror an electric component disposed at the vehicle based on the sensinginformation and the determined optimal path, to thereby cause thevehicle to perform autonomous driving according to the autonomousdriving visibility information; updating the optimal path based ondynamic information related to a movable object located in the optimalpath and the autonomous driving visibility information; receivingdifferent types of sensor data from a plurality of sensors disposed atthe vehicle; updating at least one of the autonomous driving visibilityinformation or the optimal path based on information generated bycombining at least two types of sensor data; and fusing sensor data in adifferent manner according to a sensing range of each of the pluralityof sensors, a first sensor of the plurality of sensors having a sensingrange of a first radius based on the vehicle, a second sensor of theplurality of sensors having a sensing range of a second radius, and thesecond radius being longer than the first radius from a location of thevehicle, wherein fusing the sensor data comprises: fusing sensor datasensed by the first sensor and the second sensor up to the first radiusto update the optimal path using the fused sensor data, and whereinupdating the optimal path comprises: updating the optimal path onlyusing sensor data of the second sensor in a section between the firstradius and the second radius.
 17. The method of claim 16, furthercomprising: dividing the optimal path into a plurality of sectionsaccording to characteristics of the optimal path; determining one ormore sensors, among the plurality of sensors, to be used in each sectionbased on a characteristic associated with each of the plurality ofsections; and updating the autonomous driving visibility informationbased on sensor data sensed by the determined one or more sensors. 18.The method of claim 17, further comprising: determining a section set touse the determined one or more sensors based on a type of each of theone or more sensors; and updating the autonomous driving visibilityinformation by fusing a plurality of sensor data acquired by the one ormore sensors, based on an arrival at the determined section.